{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 因子分析基础"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 引入常用库"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入需要的数据库\n",
    "from jqfactor import *\n",
    "from jqdata import *\n",
    "import pandas as pd\n",
    "from collections import OrderedDict  #保持Key的顺序\n",
    "from datetime import datetime,date,timedelta\n",
    "import matplotlib.pyplot as plt # 画图用\n",
    "import pickle  # 打包\n",
    "\n",
    "plt.style.use('ggplot')  # 设置图表风格\n",
    "\n",
    "import warnings  \n",
    "warnings.filterwarnings('ignore') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 工具API"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "# 获取日期列表\n",
    "# 获取每月末，季末，半年期期末日期\n",
    "def get_tradeday_list(start,end,frequency=None,count=None):\n",
    "    '''\n",
    "    satrt,end:str yyyy-mm-dd\n",
    "    frequency:str month,quarter,halfyear\n",
    "    ------------\n",
    "    return:list\n",
    "        type:str\n",
    "    '''\n",
    "    if count != None:\n",
    "        df = get_price('000001.XSHG',end_date=end,count=count)\n",
    "    else:\n",
    "        df = get_price('000001.XSHG',start_date=start,end_date=end)\n",
    "    if frequency == None or frequency =='day':\n",
    "        return list(map(lambda x:x.strftime('%Y-%m-%d'),df.index))\n",
    "    else:\n",
    "        df['year-month'] = [str(i)[0:7] for i in df.index]\n",
    "        if frequency == 'month':\n",
    "            return list(map(lambda x:x.strftime('%Y-%m-%d'),df.drop_duplicates('year-month',keep='last').index))\n",
    "        elif frequency == 'quarter':\n",
    "            df['month'] = [str(i)[5:7] for i in df.index]\n",
    "            df = df[(df['month']=='03') | (df['month']=='06') | (df['month']=='09') | (df['month']=='12') ]\n",
    "            list(map(lambda x:x.strftime('%Y-%m-%d'),df.drop_duplicates('year-month',keep='last').index))\n",
    "        elif frequency =='halfyear':\n",
    "            df['month'] = [str(i)[5:7] for i in df.index]\n",
    "            df = df[(df['month']=='06') | (df['month']=='12')]\n",
    "            return list(map(lambda x:x.strftime('%Y-%m-%d'),df.drop_duplicates('year-month',keep='last').index))\n",
    "\n",
    "\n",
    "# 获取回测区间内每个交易日满足筛选条件的股票池\n",
    "def get_stocks(index,traDate):\n",
    "    '''\n",
    "    index:str 指数代码\n",
    "    traDate:str yyyy-mm-dd\n",
    "    -------\n",
    "    return:list 返回成分股中剔除st后的股票\n",
    "    '''\n",
    "    index_stocks_all=get_index_stocks(index, date=traDate) # 获取指数成分股\n",
    "    # 除去成分股中的ST股票\n",
    "    is_st=get_extras('is_st', index_stocks_all, end_date=traDate, count=1).iloc[0]\n",
    "    unst_stocks=is_st[is_st!=True].index.tolist() # 获取不为st的股票\n",
    "    # 筛选大于1年的股票\n",
    "    stock_list=[]\n",
    "    traDate=datetime.strptime(traDate,'%Y-%m-%d').date()\n",
    "    for stock in unst_stocks:\n",
    "        start_date = get_security_info(stock).start_date\n",
    "        if start_date < (traDate - timedelta(days=365)):\n",
    "            stock_list.append(stock)\n",
    "    # 过滤掉当日停牌的股票\n",
    "    ## 得到是否停牌信息的dataframe，停牌的1，未停牌得0\n",
    "    suspened_info_df=get_price(stock_list,end_date=traDate,count=1,fields='paused')['paused'].T\n",
    "    ## 过滤停牌股票\n",
    "    unsuspened_index = suspened_info_df.iloc[:,0]<1\n",
    "    ## # 得到当日未停牌股票的代码list\n",
    "    unsuspened_stocks = suspened_info_df[unsuspened_index].index\n",
    "    \n",
    "    return list(unsuspened_stocks)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ===初始化===="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date_list:\n",
      "['2007-01-31', '2007-02-28', '2007-03-30', '2007-04-30', '2007-05-31', '2007-06-29', '2007-07-31', '2007-08-31', '2007-09-28', '2007-10-31', '2007-11-30', '2007-12-28', '2008-01-31', '2008-02-29', '2008-03-31', '2008-04-30', '2008-05-30', '2008-06-30', '2008-07-31', '2008-08-29', '2008-09-26', '2008-10-31', '2008-11-28', '2008-12-31', '2009-01-23', '2009-02-27', '2009-03-31', '2009-04-30', '2009-05-27', '2009-06-30', '2009-07-31', '2009-08-31', '2009-09-30', '2009-10-30', '2009-11-30', '2009-12-31', '2010-01-29', '2010-02-26', '2010-03-31', '2010-04-30', '2010-05-31', '2010-06-30', '2010-07-30', '2010-08-31', '2010-09-30', '2010-10-29', '2010-11-30', '2010-12-31', '2011-01-31', '2011-02-28', '2011-03-31', '2011-04-29', '2011-05-31', '2011-06-30', '2011-07-29', '2011-08-31', '2011-09-30', '2011-10-31', '2011-11-30', '2011-12-30', '2012-01-31', '2012-02-29', '2012-03-30', '2012-04-27', '2012-05-31', '2012-06-29', '2012-07-31', '2012-08-31', '2012-09-28', '2012-10-31', '2012-11-30', '2012-12-31', '2013-01-31', '2013-02-28', '2013-03-29', '2013-04-26', '2013-05-31', '2013-06-28', '2013-07-31', '2013-08-30', '2013-09-30', '2013-10-31', '2013-11-29', '2013-12-31', '2014-01-30', '2014-02-28', '2014-03-31', '2014-04-30', '2014-05-30', '2014-06-30', '2014-07-31', '2014-08-29', '2014-09-30', '2014-10-31', '2014-11-28', '2014-12-31', '2015-01-30', '2015-02-27', '2015-03-31', '2015-04-30', '2015-05-29', '2015-06-30', '2015-07-31', '2015-08-31', '2015-09-30', '2015-10-30', '2015-11-30', '2015-12-31', '2016-01-29', '2016-02-29', '2016-03-31', '2016-04-29', '2016-05-31', '2016-06-30', '2016-07-29', '2016-08-31', '2016-09-30', '2016-10-31', '2016-11-30', '2016-12-30', '2017-01-26', '2017-02-28', '2017-03-31', '2017-04-28', '2017-05-31', '2017-06-30', '2017-07-31', '2017-08-31', '2017-09-29', '2017-10-31', '2017-11-30', '2017-12-29', '2018-01-31', '2018-02-28', '2018-03-30', '2018-04-27', '2018-05-31', '2018-06-29', '2018-07-31', '2018-08-31', '2018-09-28', '2018-10-31', '2018-11-30', '2018-12-28', '2019-01-31', '2019-02-28', '2019-03-29', '2019-04-30', '2019-05-31', '2019-06-28', '2019-07-01']\n",
      "--------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "# 设置起止时间\n",
    "## 中证开始日期为2007-01-15\n",
    "start='2007-01-15'\n",
    "end='2019-07-01'\n",
    "\n",
    "#获取日期列表\n",
    "date_list = get_tradeday_list(start=start,end=end,frequency='month')#获取回测日期间的所有交易日\n",
    "\n",
    "print('date_list:\\n%s'%(date_list))\n",
    "print('-'*80)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ===原始计算因子数据===\n",
    "\n",
    "- 进行因子值函数定义\n",
    "- 循环日期获取因子值\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "股票价格的动量（Momentum） ， 顾名思义代表的是股价在一定时间内延续前期走势的现象。 不过与海外长期的研究和经验相悖的是， 在 A 股市场， 我们发现股价的反转（Reverse） 效应要远强于动量效应， 且短期反转因子的历史收益非常出色。\n",
    "\n",
    "但常用动量因子也存在单调性不佳， 多头收益不稳定的问题， 因此参考研报我们尝试从不同角度出发对动量因子进行改造， 寻找提升常用动量因子选股\n",
    "效果和稳定性的方法。\n"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在该多因子系列报告中， 曾给出过动量类因子的因子测试结论， 报告中测试的几个常用动量因子，也是我们经常接触到的基础动量因子，明细如下\n",
    "\n",
    "![image.png](attachment:image.png)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "根据研报的观点，动量（反转） 效应的成因是投资者认识出现偏差，对信息的解读不够及时充分。 也可以认为动量（反转） 效应是来自于投资者认知偏差或者说噪音交易行为。\n",
    "\n",
    "由此可以推测， 散户集中程度或者说流动性因素是影响动量因子效果的一个重要变量。 因此， 我们会自然的联想到采用截面中性化的方法， 将衡量散户集中程度的流动性因素从原始动量因子中剥离。\n",
    "\n",
    "我们在构造因子时按申万一级行,对数流通市值对因子进行中性化处理。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下面我们将以统计周期为20,60,120,240,480日的动量因子为例进行探索演示\n",
    "\n",
    "- 测试区间：2017-01-15至2019-07-01\n",
    "- 股票池：中证500成分股(剔除选股日ST股票;剔除上市不满一年的股票;过滤掉当日停牌的股票)\n",
    "- 因子中性化：市值、申万一级行业\n",
    "- 调仓频率：月度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "## 提取数据并计算动量因子-获取基础动量因子\n",
    "def get_momentum_factor(dates,N,neutralize_=True): \n",
    "    '''\n",
    "    N：int\n",
    "    输入参数N为各调仓日前推N日的交易日期,dates为回测期内各个月末交易日（也就是调仓日）\n",
    "    dates:list\n",
    "    neutralize:bool 是否中性化\n",
    "    -------------\n",
    "    return:DataFrame\n",
    "    已中性化momentum_N,risk数据：按申万一级行,对数流通市值中性化\n",
    "    数据结构：\n",
    "    |index-date|index-code|values-returns|values-risk|\n",
    "    '''\n",
    "    dict_=OrderedDict() # 创建每期存取数据字典\n",
    "    \n",
    "    for date in dates:\n",
    "        \n",
    "        stocks=get_stocks('000905.XSHG',date)  # 提取各交易日的成分股中满足筛选条件的股票池\n",
    "        # step1:计算股票过去N日的收益率\n",
    "        ## 提取各股票过去N个交易日的涨跌幅，即为过去N日内的收益率\n",
    "        close=get_price(stocks,end_date=date,count=N,fields='close').close\n",
    "        # 计算对数收益率\n",
    "        log_ret=np.log(close)\n",
    "        log_ret=log_ret.diff() #df\n",
    "        # N日收益率=基础动量因子\n",
    "        returns=log_ret.sum() #series\n",
    "        \n",
    "        # step2:计算股票过去N日的收益波动率，即日收益率的标准差\n",
    "        # 提取股票过去N日的收益波动率\n",
    "        sigma=log_ret.std() #series\n",
    "        sigma.name='risk'\n",
    "        \n",
    "        # 是否中性化\n",
    "        if neutralize_:\n",
    "            # 收益按申万一级行,对数流通市值中性化因子\n",
    "            returns_neutralize=neutralize(returns,how=['sw_l1','ln_circulating_market_cap'],date=date,fillna='sw_l1')\n",
    "            returns_neutralize.name='returns'\n",
    "        else:\n",
    "            returns_neutralize=returns\n",
    "            returns_neutralize.name='returns'\n",
    "    \n",
    "        # step3:计算升级动量因子\n",
    "        data=pd.concat([returns_neutralize,sigma],axis=1,join='inner')  #将收益率与风险合并\n",
    "        data['momentum']=data['returns']-3000*(data['risk']**2)  #计算动量因子\n",
    "        \n",
    "        print(date,'success')\n",
    "        dict_[datetime.strptime(date,\"%Y-%m-%d\")]=data\n",
    "        \n",
    "    datas=pd.concat(dict_.values(),keys=dict_.keys())\n",
    "    datas.index.names=['date','codes']\n",
    "    return datas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 此处数据提取需花费较多时间\n",
    "## 将基础版动量策略的原始数据存入数据文件中，便于后期读取\n",
    "momentum_1M_datas=get_momentum_factor(date_list,20,False)  \n",
    "momentum_3M_datas=get_momentum_factor(date_list,60,False)  \n",
    "momentum_6M_datas=get_momentum_factor(date_list,120,False)  \n",
    "momentum_12M_datas=get_momentum_factor(date_list,240,False)  \n",
    "momentum_24M_datas=get_momentum_factor(date_list,480,False)  \n",
    "\n",
    "# 构建字典\n",
    "k=['1M','3M','6M','12M','24M']\n",
    "v=[momentum_1M_datas,momentum_3M_datas,momentum_6M_datas,\n",
    "   momentum_12M_datas,momentum_24M_datas]\n",
    "momentum_factor=dict(zip(k,v))\n",
    "\n",
    "# 把计算出的因子数据写入文件 方便后续调用\n",
    "pkl_file = open('momentum_factor.pkl', 'wb')\n",
    "pickle.dump(momentum_factor, pkl_file, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "momentum_1M_datas\n",
      "\n",
      " ---------------------------------------- \n",
      "                          returns      risk  momentum\n",
      "date       codes                                    \n",
      "2007-01-31 000006.XSHE -0.134222  0.010151 -0.443372\n",
      "           000016.XSHE  0.134819  0.006959 -0.010449\n",
      "           000028.XSHE  0.214434  0.008959 -0.026373\n",
      "           000032.XSHE  0.180670  0.007696  0.002975\n",
      "           000033.XSHE  0.217269  0.006701  0.082546 \n",
      "\n",
      "momentum_3M_datas\n",
      "\n",
      " ---------------------------------------- \n",
      "                          returns      risk  momentum\n",
      "date       codes                                    \n",
      "2007-01-31 000006.XSHE  0.214890  0.014258 -0.395001\n",
      "           000016.XSHE  0.104360  0.009273 -0.153609\n",
      "           000028.XSHE  0.270524  0.012218 -0.177326\n",
      "           000032.XSHE  0.170818  0.009664 -0.109344\n",
      "           000033.XSHE  0.144656  0.010459 -0.183495 \n",
      "\n",
      "momentum_6M_datas\n",
      "\n",
      " ---------------------------------------- \n",
      "                          returns      risk  momentum\n",
      "date       codes                                    \n",
      "2007-01-31 000006.XSHE  0.362215  0.016235 -0.428546\n",
      "           000016.XSHE  0.084557  0.010882 -0.270721\n",
      "           000028.XSHE  0.513840  0.015007 -0.161788\n",
      "           000032.XSHE  0.299691  0.012241 -0.149828\n",
      "           000033.XSHE  0.332440  0.013342 -0.201568 \n",
      "\n",
      "momentum_12M_datas\n",
      "\n",
      " ---------------------------------------- \n",
      "                          returns      risk  momentum\n",
      "date       codes                                    \n",
      "2007-01-31 000006.XSHE  0.755846  0.023466 -0.896121\n",
      "           000016.XSHE  0.446850  0.015969 -0.318176\n",
      "           000028.XSHE  0.951906  0.022520 -0.569518\n",
      "           000032.XSHE  0.183976  0.018703 -0.865447\n",
      "           000033.XSHE  0.552069  0.023367 -1.085961 \n",
      "\n",
      "momentum_24M_datas\n",
      "\n",
      " ---------------------------------------- \n",
      "                          returns      risk  momentum\n",
      "date       codes                                    \n",
      "2007-01-31 000006.XSHE  1.191164  0.030351 -1.572329\n",
      "           000016.XSHE  0.145182  0.020839 -1.157593\n",
      "           000028.XSHE  0.993703  0.026028 -1.038631\n",
      "           000032.XSHE  0.126082  0.024951 -1.741569\n",
      "           000033.XSHE  0.489725  0.029222 -2.072112 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "# 读取因子数据文件\n",
    "pkl_file = open('momentum_factor.pkl', 'rb')\n",
    "momentum_factor = pickle.load(pkl_file)\n",
    "pkl_file.close()\n",
    "\n",
    "# 数据一览\n",
    "print('momentum_1M_datas\\n\\n','-'*40,'\\n',momentum_factor['1M'].head(),'\\n')\n",
    "print('momentum_3M_datas\\n\\n','-'*40,'\\n',momentum_factor['3M'].head(),'\\n')\n",
    "print('momentum_6M_datas\\n\\n','-'*40,'\\n',momentum_factor['6M'].head(),'\\n')\n",
    "print('momentum_12M_datas\\n\\n','-'*40,'\\n',momentum_factor['12M'].head(),'\\n')\n",
    "print('momentum_24M_datas\\n\\n','-'*40,'\\n',momentum_factor['24M'].head(),'\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 因子效果检查\n",
    "\n",
    "\n",
    "我们将通过如下三个方面进行因子效果检查\n",
    "\n",
    "1.IC信息比率\n",
    "\n",
    "2.分组收益\n",
    "\n",
    "3.换手率\n",
    "\n",
    "在收益分析中, 分位数的平均收益， 第一分位数的因子值最小， 第十分位数的因子值最大。\n",
    "\n",
    "分位数收益： 表示持仓1月后，各分位数可以获得的平均收益。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 基础动量因子"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 使用获取的因子值进行单因子分析\n",
    "## 设置调仓周期\n",
    "periods=20 # (5,10,20)\n",
    "## 设置分层数量\n",
    "quantiles=10\n",
    "## 分析\n",
    "far_1M = analyze_factor(factor=momentum_factor['1M'].loc[:,'returns'], start_date=start, end_date=end, weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)\n",
    "far_3M = analyze_factor(factor=momentum_factor['3M'].loc[:,'returns'], start_date=start, end_date=end, weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)\n",
    "far_6M = analyze_factor(factor=momentum_factor['6M'].loc[:,'returns'], start_date=start, end_date=end, weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)\n",
    "far_12M = analyze_factor(factor=momentum_factor['12M'].loc[:,'returns'], start_date=start, end_date=end, weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)\n",
    "far_24M = analyze_factor(factor=momentum_factor['24M'].loc[:,'returns'], start_date=start, end_date=end, weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 因子分析字典\n",
    "k=['1M','3M','6M','12M','24M']\n",
    "v=[far_1M,far_3M,far_6M,far_12M,far_24M]\n",
    "basic_far=dict(zip(k,v))\n",
    "# 保存分析后的数据\n",
    "pkl_file = open('basic_far.pkl', 'wb')\n",
    "pickle.dump(basic_far, pkl_file, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取分析文件\n",
    "pkl_file = open('basic_far.pkl', 'rb')\n",
    "basic_far = pickle.load(pkl_file)\n",
    "pkl_file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IC分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 计算M1,M3,M6,M12,M24的IC Mean\n",
    "ic_mean_m1=basic_far['1M'].calc_mean_information_coefficient(method='rank')\n",
    "ic_mean_m3=basic_far['3M'].calc_mean_information_coefficient(method='rank')\n",
    "ic_mean_m6=basic_far['6M'].calc_mean_information_coefficient(method='rank')\n",
    "ic_mean_m12=basic_far['12M'].calc_mean_information_coefficient(method='rank')\n",
    "ic_mean_m24=basic_far['24M'].calc_mean_information_coefficient(method='rank')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "各因子分组IC Mean情况\n",
      " ------------------------------------------------------------ \n",
      "                  M1       M3        M6       M12       M24\n",
      "period_20 -0.066641 -0.07017 -0.052533 -0.052422 -0.052505 \n",
      " ------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "ic_mean=pd.concat([ic_mean_m1,ic_mean_m3,ic_mean_m6,ic_mean_m12,ic_mean_m24],axis=1)\n",
    "ic_mean.columns=['M1','M3','M6','M12','M24']\n",
    "print('各因子分组IC Mean情况\\n','-'*60,'\\n',ic_mean,'\\n','-'*60)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由下图为M1,M3,M6,M12,M24动量因子的IC Mean图表，整体上看，动量因子在中证500中均有显著的反向收益，既前期涨幅越高的股票，未来一个月收益表现越差。\n",
    "\n",
    "无论是长周期(M24)还是短周期(M1),都具有显著的负向预测效果，且IC Mean均小于0.04。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"\\nplt.figure(2,figsize=(12,5))\\nplt.bar(ic_mean.columns,ic_mean.values[1],align='center', alpha=0.5)\\nplt.title('period10 IC_MEAN',fontsize=18)\\nplt.figure(3,figsize=(12,5))\\nplt.bar(ic_mean.columns,ic_mean.values[2],align='center', alpha=0.5)\\nplt.title('period20 IC_MEAN',fontsize=18)\\n\""
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 对IC Mean信息画图\n",
    "plt.figure(1,figsize=(12,5))\n",
    "plt.bar(ic_mean.columns,ic_mean.values[0],align='center', alpha=0.5)\n",
    "plt.title('IC_MEAN',fontsize=18)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 动量因子测试数据汇总表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 汇总因子测试数据\n",
    "def factor_report(far):\n",
    "    '''\n",
    "    far:为因子分析后的数据类型\n",
    "    ---------\n",
    "    return:dataframe\n",
    "    '''\n",
    "    # 获取最大百分位组减最小百分位组的收益率及标准差(超额收益)\n",
    "    mean, std = far.compute_mean_returns_spread (by_date=False, demeaned=1)\n",
    "    # 计算每组的夏普-按调仓\n",
    "    longshort_sharpe=mean/std\n",
    "    # 计算Mono_score(超额收益)\n",
    "    ## 因子为升序排列10因子最大，1最小，研报中10组为降序\n",
    "    ## MONO_Score，主要组别情况\n",
    "    Numerator_mean, _ = far.compute_mean_returns_spread (upper_quant=1,lower_quant=10,by_date=False,demeaned=1)\n",
    "    Denominator_mean,_=far.compute_mean_returns_spread (upper_quant=3,lower_quant=8,by_date=False, demeaned=1)\n",
    "    MONO_Score=Numerator_mean/Denominator_mean\n",
    "    # IC_IR\n",
    "    IC_IR=far.calc_mean_information_coefficient(method='rank')\n",
    "    IC=far.calc_mean_information_coefficient(method='normal')\n",
    "    # 换手率\n",
    "    ## 计算每组持仓的平均换手率\n",
    "    v=[]\n",
    "    data_dic=far.quantile_turnover\n",
    "    periods=data_dic.keys()\n",
    "    for period in periods:\n",
    "        temp=data_dic[period].mean()\n",
    "        v.append(temp.mean())\n",
    "    turnover=pd.Series(v,index=periods)\n",
    "    report=pd.concat([IC,IC_IR,longshort_sharpe,MONO_Score,turnover],axis=1)\n",
    "    report.columns=['IC','IC_IR','LongShort_sharpe','MONO_Score','Turnover']\n",
    "    return report\n",
    "\n",
    "# 查看持仓周期报告\n",
    "def trans2period(fardic,period):\n",
    "    '''\n",
    "    fardic:dic,key为far名称,为far数据\n",
    "    period：为调仓周期\n",
    "    ---------\n",
    "    return:dataframe\n",
    "    '''\n",
    "    rList=[]\n",
    "    for farname,farvalue in fardic.items():\n",
    "        r_x=factor_report(farvalue).loc['period_'+str(period)]\n",
    "        r_x.name=farname\n",
    "        rList.append(r_x)\n",
    "    datas=pd.concat(rList,axis=1)\n",
    "    return datas.T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "调仓周期为5,10,20天的测试结果如下,从表格中我们可以看到无论哪个持仓周期，结果均为：动量因子(反正因子)3M的收益率较高,多空收益的稳定性较差，因子单调性(MONO_Score)不太稳定，换手率较高。\n",
    "\n",
    "**PS:MONO_Score的构造为（第1组年化收益-10组年化收益）/（3组年化收益-8组年化收益**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IC</th>\n",
       "      <th>IC_IR</th>\n",
       "      <th>LongShort_sharpe</th>\n",
       "      <th>MONO_Score</th>\n",
       "      <th>Turnover</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1M</th>\n",
       "      <td>-0.045512</td>\n",
       "      <td>-0.066641</td>\n",
       "      <td>-7.728916</td>\n",
       "      <td>2.012446</td>\n",
       "      <td>0.930497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3M</th>\n",
       "      <td>-0.051130</td>\n",
       "      <td>-0.070170</td>\n",
       "      <td>-8.563511</td>\n",
       "      <td>3.274893</td>\n",
       "      <td>0.927089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6M</th>\n",
       "      <td>-0.038093</td>\n",
       "      <td>-0.052533</td>\n",
       "      <td>-6.561318</td>\n",
       "      <td>2.959917</td>\n",
       "      <td>0.927962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12M</th>\n",
       "      <td>-0.038740</td>\n",
       "      <td>-0.052422</td>\n",
       "      <td>-8.121832</td>\n",
       "      <td>3.550794</td>\n",
       "      <td>0.931315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24M</th>\n",
       "      <td>-0.033047</td>\n",
       "      <td>-0.052505</td>\n",
       "      <td>-7.064040</td>\n",
       "      <td>2.363961</td>\n",
       "      <td>0.932651</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           IC     IC_IR  LongShort_sharpe  MONO_Score  Turnover\n",
       "1M  -0.045512 -0.066641         -7.728916    2.012446  0.930497\n",
       "3M  -0.051130 -0.070170         -8.563511    3.274893  0.927089\n",
       "6M  -0.038093 -0.052533         -6.561318    2.959917  0.927962\n",
       "12M -0.038740 -0.052422         -8.121832    3.550794  0.931315\n",
       "24M -0.033047 -0.052505         -7.064040    2.363961  0.932651"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 各因子获取20日调仓周期因子回测数据\n",
    "trans2period(basic_far,20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "进一步分析可以发现3M因子的超额收益率，仅20日调仓周期中的7-10组单调性较高，其他组别单调性较差。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 分位数收益率\n",
    "basic_far['3M'].plot_quantile_returns_bar(demeaned=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 动量因子改进思路"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "上文对常见的动量因子做了比较深入的分析，也可以发现动量因子的确具 有很高的IC绝对值和IC_IR绝对值，空头组的负向收益显著，但也存在单调性\n",
    "不稳定、多头超额不显著的缺点。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下文中我们将从四个不同的角度入手，尝试对动量因子进行改造，已求寻 找到更为稳健的动量因子："
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.结合均线的趋势动量因子"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "动量因子构造时所使用的数据仅为`起始节点和末尾节点的股价数据`，对于期间的股价信息并未充分反应，因此我们尝试*采用均线*的思路，构造更好的反应股价趋势的趋势动量因子。\n",
    "\n",
    "$MA_{jt,L}=\\frac{P^{t}_{j,d-L+1}+P^{t}_{j,d-L+2}+\\ldots+P^{t}_{j,d-1}+P^{t}_{j,d}}{L}$\n",
    "\n",
    "$P^{t}_{j,d}$是指j股票在t月的每个交易日的收盘价，L是移动平均的窗口宽度。为了使得我们得到的信号是一个平稳序列，同时截面上横向可比，将移动 平均价格序列除以d日的收盘价，做标准化处理\n",
    "\n",
    "$\\widetilde{MA_{jt,L}}=\\frac{MA_{jt,L}}{p^{t}_{j,d}}$\n",
    "\n",
    "移动平均 MA 这个指标来用来识别股票未来一段时间的价格趋势，为了更 好地利用移动平均数，我们可以使用价格来将移动平均数标准化，这样就能够\n",
    "将均线转化为一个截面可比的用来反应股价变化趋势的指标。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.1趋势动量因子：单调性较好"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在参数的设置上，我们参照常用动量因子的时长参数，选取20、60、120、 240日移动平均趋势动量因子做测试。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_momentum_mono_factor(dates,N):\n",
    "    '''\n",
    "    输入参数dates_befN_为各调仓日前推N日的交易日期， dates为回测期内各个月末交易日（也就是调仓日）\n",
    "    dates_befN_:list\n",
    "    dates:list\n",
    "    -------------\n",
    "    return:DataFrame\n",
    "    |index-date|index-code|values|\n",
    "    '''\n",
    "    dict_=OrderedDict() # 创建每期存取数据字典\n",
    "    for date in dates:\n",
    "        \n",
    "        stocks=get_stocks('000905.XSHG',date)  # 提取各交易日的成分股中满足筛选条件的股票池\n",
    "        # step1:计算股票过去N日的收益率\n",
    "        ## 提取各股票过去N个交易日的涨跌幅，即为过去N日内的收益率\n",
    "        close=get_price(stocks,end_date=date,count=N,fields='close').close\n",
    "        # step2:计算移动平均值\n",
    "        ## 计算移动平均数\n",
    "        MA_N=close.rolling(N).mean()\n",
    "        # step3:标准化\n",
    "        Z_MA=MA_N/close.loc[date]\n",
    "        data=Z_MA.loc[date]\n",
    "        data.name='MA_'+str(N)\n",
    "        print(date,'success')\n",
    "        dict_[datetime.strptime(date,\"%Y-%m-%d\")]=data\n",
    "    datas=pd.concat(dict_.values(),keys=dict_.keys())\n",
    "    datas=pd.DataFrame(datas)\n",
    "    datas.index.names=['date','codes']\n",
    "    return datas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2007-01-31 success\n",
      "2007-02-28 success\n",
      "2007-03-30 success\n",
      "2007-04-30 success\n",
      "2007-05-31 success\n",
      "2007-06-29 success\n",
      "2007-07-31 success\n",
      "2007-08-31 success\n",
      "2007-09-28 success\n",
      "2007-10-31 success\n",
      "2007-11-30 success\n",
      "2007-12-28 success\n",
      "2008-01-31 success\n",
      "2008-02-29 success\n",
      "2008-03-31 success\n",
      "2008-04-30 success\n",
      "2008-05-30 success\n",
      "2008-06-30 success\n",
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   "source": [
    "# 此处数据提取需花费较多时间\n",
    "## 将提升版动量策略的原始数据存入数据文件中，便于后期读取\n",
    "momentum_mono_1M_datas=get_momentum_mono_factor(date_list,20)\n",
    "momentum_mono_3M_datas=get_momentum_mono_factor(date_list,60)  \n",
    "momentum_mono_6M_datas=get_momentum_mono_factor(date_list,120)  \n",
    "momentum_mono_12M_datas=get_momentum_mono_factor(date_list,240)  \n",
    "\n",
    "\n",
    "# 构建字典\n",
    "k=['Mono_1M','Mono_3M','Mono_6M','Mono_12M']\n",
    "v=[momentum_mono_1M_datas,momentum_mono_3M_datas,momentum_mono_6M_datas,\n",
    "   momentum_mono_12M_datas]\n",
    "mono_factor=dict(zip(k,v))\n",
    "\n",
    "# 把计算出的因子数据写入文件 方便后续调用\n",
    "pkl_file = open('mono_factor.pkl', 'wb')\n",
    "pickle.dump(mono_factor, pkl_file, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取因子数据文件\n",
    "pkl_file = open('mono_factor.pkl', 'rb')\n",
    "mono_factor = pickle.load(pkl_file)\n",
    "pkl_file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 使用获取的因子值进行单因子分析\n",
    "## 设置调仓周期\n",
    "periods=20\n",
    "## 设置分层数量\n",
    "quantiles=10\n",
    "## 分析\n",
    "far_mono_1M = analyze_factor(factor=mono_factor['Mono_1M'].MA_20, start_date=start, end_date=end, weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)\n",
    "far_mono_3M = analyze_factor(factor=mono_factor['Mono_3M'].MA_60, start_date=start, end_date=end, weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)\n",
    "far_mono_6M = analyze_factor(factor=mono_factor['Mono_6M'].MA_120, start_date=start, end_date=end, weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)\n",
    "far_mono_12M = analyze_factor(factor=mono_factor['Mono_12M'].MA_240, start_date=start, end_date=end, weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 构建因子分析字典\n",
    "k=['Mono_1M','Mono_3M','Mono_6M','Mono_12M']\n",
    "v=[far_mono_1M,far_mono_3M,far_mono_6M,far_mono_12M]\n",
    "mono_far=dict(zip(k,v))\n",
    "# 保存分析后的数据\n",
    "pkl_file = open('mono_far.pkl', 'wb')\n",
    "pickle.dump(mono_far, pkl_file, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取分析文件\n",
    "pkl_file = open('mono_far.pkl', 'rb')\n",
    "mono_far = pickle.load(pkl_file)\n",
    "pkl_file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "月度调仓周期中Mini_3M的收益率最高，多空组合的夏普达到了了12.2，单调性得分兵不高，仅Mono_12M超过了3分。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IC</th>\n",
       "      <th>IC_IR</th>\n",
       "      <th>LongShort_sharpe</th>\n",
       "      <th>MONO_Score</th>\n",
       "      <th>Turnover</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Mono_1M</th>\n",
       "      <td>0.039852</td>\n",
       "      <td>0.056369</td>\n",
       "      <td>8.450311</td>\n",
       "      <td>1.876048</td>\n",
       "      <td>0.930611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono_3M</th>\n",
       "      <td>0.051695</td>\n",
       "      <td>0.076417</td>\n",
       "      <td>10.843270</td>\n",
       "      <td>1.824382</td>\n",
       "      <td>0.929609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono_6M</th>\n",
       "      <td>0.053139</td>\n",
       "      <td>0.074074</td>\n",
       "      <td>11.392015</td>\n",
       "      <td>2.818863</td>\n",
       "      <td>0.926554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono_12M</th>\n",
       "      <td>0.045672</td>\n",
       "      <td>0.064755</td>\n",
       "      <td>10.714378</td>\n",
       "      <td>3.184995</td>\n",
       "      <td>0.929737</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                IC     IC_IR  LongShort_sharpe  MONO_Score  Turnover\n",
       "Mono_1M   0.039852  0.056369          8.450311    1.876048  0.930611\n",
       "Mono_3M   0.051695  0.076417         10.843270    1.824382  0.929609\n",
       "Mono_6M   0.053139  0.074074         11.392015    2.818863  0.926554\n",
       "Mono_12M  0.045672  0.064755         10.714378    3.184995  0.929737"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trans2period(mono_far,20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下图中可以看出Mono_3M因子1至5组的超额收益率单调性较高，6至10组单调性较弱。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 分位数收益率\n",
    "mono_far['Mono_3M'].plot_quantile_returns_bar(demeaned=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "趋势动量因子月度IC序列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# IC序列\n",
    "mono_far['Mono_3M'].plot_ic_ts(method='rank')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.剥离流动性因素后的提纯动量因子"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "到采用截面中性化的方法，将衡量散户 集中程度的流动性因素从原始动量因子中剥离"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2007-01-31 success\n",
      "2007-02-28 success\n",
      "2007-03-30 success\n",
      "2007-04-30 success\n",
      "2007-05-31 success\n",
      "2007-06-29 success\n",
      "2007-07-31 success\n",
      "2007-08-31 success\n",
      "2007-09-28 success\n",
      "2007-10-31 success\n",
      "2007-11-30 success\n",
      "2007-12-28 success\n",
      "2008-01-31 success\n",
      "2008-02-29 success\n",
      "2008-03-31 success\n",
      "2008-04-30 success\n",
      "2008-05-30 success\n",
      "2008-06-30 success\n",
      "2008-07-31 success\n",
      "2008-08-29 success\n",
      "2008-09-26 success\n",
      "2008-10-31 success\n",
      "2008-11-28 success\n",
      "2008-12-31 success\n",
      "2009-01-23 success\n",
      "2009-02-27 success\n",
      "2009-03-31 success\n",
      "2009-04-30 success\n",
      "2009-05-27 success\n",
      "2009-06-30 success\n",
      "2009-07-31 success\n",
      "2009-08-31 success\n",
      "2009-09-30 success\n",
      "2009-10-30 success\n",
      "2009-11-30 success\n",
      "2009-12-31 success\n",
      "2010-01-29 success\n",
      "2010-02-26 success\n",
      "2010-03-31 success\n",
      "2010-04-30 success\n",
      "2010-05-31 success\n",
      "2010-06-30 success\n",
      "2010-07-30 success\n",
      "2010-08-31 success\n",
      "2010-09-30 success\n",
      "2010-10-29 success\n",
      "2010-11-30 success\n",
      "2010-12-31 success\n",
      "2011-01-31 success\n",
      "2011-02-28 success\n",
      "2011-03-31 success\n",
      "2011-04-29 success\n",
      "2011-05-31 success\n",
      "2011-06-30 success\n",
      "2011-07-29 success\n",
      "2011-08-31 success\n",
      "2011-09-30 success\n",
      "2011-10-31 success\n",
      "2011-11-30 success\n",
      "2011-12-30 success\n",
      "2012-01-31 success\n",
      "2012-02-29 success\n",
      "2012-03-30 success\n",
      "2012-04-27 success\n",
      "2012-05-31 success\n",
      "2012-06-29 success\n",
      "2012-07-31 success\n",
      "2012-08-31 success\n",
      "2012-09-28 success\n",
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      "2013-01-31 success\n",
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      "2013-08-30 success\n",
      "2013-09-30 success\n",
      "2013-10-31 success\n",
      "2013-11-29 success\n",
      "2013-12-31 success\n",
      "2014-01-30 success\n",
      "2014-02-28 success\n",
      "2014-03-31 success\n",
      "2014-04-30 success\n",
      "2014-05-30 success\n",
      "2014-06-30 success\n",
      "2014-07-31 success\n",
      "2014-08-29 success\n",
      "2014-09-30 success\n",
      "2014-10-31 success\n",
      "2014-11-28 success\n",
      "2014-12-31 success\n",
      "2015-01-30 success\n",
      "2015-02-27 success\n",
      "2015-03-31 success\n",
      "2015-04-30 success\n",
      "2015-05-29 success\n",
      "2015-06-30 success\n",
      "2015-07-31 success\n",
      "2015-08-31 success\n",
      "2015-09-30 success\n",
      "2015-10-30 success\n",
      "2015-11-30 success\n",
      "2015-12-31 success\n",
      "2016-01-29 success\n",
      "2016-02-29 success\n",
      "2016-03-31 success\n",
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      "2016-05-31 success\n",
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      "2016-08-31 success\n",
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      "2016-11-30 success\n",
      "2016-12-30 success\n",
      "2017-01-26 success\n",
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      "2017-03-31 success\n",
      "2017-04-28 success\n",
      "2017-05-31 success\n",
      "2017-06-30 success\n",
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      "2017-08-31 success\n",
      "2017-09-29 success\n",
      "2017-10-31 success\n",
      "2017-11-30 success\n",
      "2017-12-29 success\n",
      "2018-01-31 success\n",
      "2018-02-28 success\n",
      "2018-03-30 success\n",
      "2018-04-27 success\n",
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      "2018-06-29 success\n",
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      "2018-08-31 success\n",
      "2018-09-28 success\n",
      "2018-10-31 success\n",
      "2018-11-30 success\n",
      "2018-12-28 success\n",
      "2019-01-31 success\n",
      "2019-02-28 success\n",
      "2019-03-29 success\n",
      "2019-04-30 success\n",
      "2019-05-31 success\n",
      "2019-06-28 success\n",
      "2019-07-01 success\n",
      "2007-01-31 success\n",
      "2007-02-28 success\n",
      "2007-03-30 success\n",
      "2007-04-30 success\n",
      "2007-05-31 success\n",
      "2007-06-29 success\n",
      "2007-07-31 success\n",
      "2007-08-31 success\n",
      "2007-09-28 success\n",
      "2007-10-31 success\n",
      "2007-11-30 success\n",
      "2007-12-28 success\n",
      "2008-01-31 success\n",
      "2008-02-29 success\n",
      "2008-03-31 success\n",
      "2008-04-30 success\n",
      "2008-05-30 success\n",
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      "2008-07-31 success\n",
      "2008-08-29 success\n",
      "2008-09-26 success\n",
      "2008-10-31 success\n",
      "2008-11-28 success\n",
      "2008-12-31 success\n",
      "2009-01-23 success\n",
      "2009-02-27 success\n",
      "2009-03-31 success\n",
      "2009-04-30 success\n",
      "2009-05-27 success\n",
      "2009-06-30 success\n",
      "2009-07-31 success\n",
      "2009-08-31 success\n",
      "2009-09-30 success\n",
      "2009-10-30 success\n",
      "2009-11-30 success\n",
      "2009-12-31 success\n",
      "2010-01-29 success\n",
      "2010-02-26 success\n",
      "2010-03-31 success\n",
      "2010-04-30 success\n",
      "2010-05-31 success\n",
      "2010-06-30 success\n",
      "2010-07-30 success\n",
      "2010-08-31 success\n",
      "2010-09-30 success\n",
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   ],
   "source": [
    "# 此处数据提取需花费较多时间\n",
    "## 将基础版动量策略的原始数据存入数据文件中，便于后期读取\n",
    "momentum_1M_Neu=get_momentum_factor(date_list,20,True)  \n",
    "momentum_3M_Neu=get_momentum_factor(date_list,60,True)  \n",
    "momentum_6M_Neu=get_momentum_factor(date_list,120,True)  \n",
    "momentum_12M_Neu=get_momentum_factor(date_list,240,True)  \n",
    "momentum_24M_Neu=get_momentum_factor(date_list,480,True)  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 构建字典\n",
    "k=['Neu_1M','Neu_3M','Neu_6M','Neu_12M','Neu_24M']\n",
    "v=[momentum_1M_Neu,momentum_3M_Neu,momentum_6M_Neu,momentum_12M_Neu,momentum_24M_Neu]\n",
    "Neu_fartor=dict(zip(k,v))\n",
    "\n",
    "# 把计算出的因子数据写入文件 方便后续调用\n",
    "pkl_file = open('Neu_factor.pkl', 'wb')\n",
    "pickle.dump(Neu_fartor, pkl_file, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取因子数据文件\n",
    "pkl_file = open('Neu_factor.pkl', 'rb')\n",
    "Neu_factor = pickle.load(pkl_file)\n",
    "pkl_file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 使用获取的因子值进行单因子分析\n",
    "## 设置调仓周期\n",
    "periods=20\n",
    "## 设置分层数量\n",
    "quantiles=10\n",
    "## 分析\n",
    "far_Neu_1M = analyze_factor(factor=Neu_factor['Neu_1M'].loc[:,'returns'], start_date=start, end_date=end, weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)\n",
    "far_Neu_3M = analyze_factor(factor=Neu_factor['Neu_3M'].loc[:,'returns'], start_date=start, end_date=end, weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)\n",
    "far_Neu_6M = analyze_factor(factor=Neu_factor['Neu_6M'].loc[:,'returns'], start_date=start, end_date=end, weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)\n",
    "far_Neu_12M = analyze_factor(factor=Neu_factor['Neu_12M'].loc[:,'returns'], start_date=start, end_date=end, weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)\n",
    "far_Neu_24M = analyze_factor(factor=Neu_factor['Neu_24M'].loc[:,'returns'], start_date=start, end_date=end, weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 构建字典\n",
    "k=['Neu_1M','Neu_3M','Neu_6M','Neu_12M','Neu_24M']\n",
    "v=[far_Neu_1M,far_Neu_3M,far_Neu_6M,far_Neu_12M,far_Neu_24M]\n",
    "Neu_far=dict(zip(k,v))\n",
    "\n",
    "# 保存分析后的数据\n",
    "pkl_file = open('Neu_far.pkl', 'wb')\n",
    "pickle.dump(Neu_far, pkl_file, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取分析文件\n",
    "pkl_file = open('Neu_far.pkl', 'rb')\n",
    "Neu_far = pickle.load(pkl_file)\n",
    "pkl_file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IC</th>\n",
       "      <th>IC_IR</th>\n",
       "      <th>LongShort_sharpe</th>\n",
       "      <th>MONO_Score</th>\n",
       "      <th>Turnover</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Neu_1M</th>\n",
       "      <td>-0.049441</td>\n",
       "      <td>-0.068072</td>\n",
       "      <td>-8.622452</td>\n",
       "      <td>2.194422</td>\n",
       "      <td>0.929800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Neu_3M</th>\n",
       "      <td>-0.047448</td>\n",
       "      <td>-0.061655</td>\n",
       "      <td>-8.362406</td>\n",
       "      <td>2.650140</td>\n",
       "      <td>0.929090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Neu_6M</th>\n",
       "      <td>-0.038114</td>\n",
       "      <td>-0.051695</td>\n",
       "      <td>-7.495754</td>\n",
       "      <td>2.562544</td>\n",
       "      <td>0.930529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Neu_12M</th>\n",
       "      <td>-0.031491</td>\n",
       "      <td>-0.043567</td>\n",
       "      <td>-5.630657</td>\n",
       "      <td>2.577352</td>\n",
       "      <td>0.932615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Neu_24M</th>\n",
       "      <td>-0.030253</td>\n",
       "      <td>-0.045131</td>\n",
       "      <td>-7.141141</td>\n",
       "      <td>2.151828</td>\n",
       "      <td>0.931270</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               IC     IC_IR  LongShort_sharpe  MONO_Score  Turnover\n",
       "Neu_1M  -0.049441 -0.068072         -8.622452    2.194422  0.929800\n",
       "Neu_3M  -0.047448 -0.061655         -8.362406    2.650140  0.929090\n",
       "Neu_6M  -0.038114 -0.051695         -7.495754    2.562544  0.930529\n",
       "Neu_12M -0.031491 -0.043567         -5.630657    2.577352  0.932615\n",
       "Neu_24M -0.030253 -0.045131         -7.141141    2.151828  0.931270"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 去流动性因子信息\n",
    "trans2period(Neu_far,20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.1提纯动量因子单调性提升明显，多空年化收益提高"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "将因子做中性化处理，剥离 流动性对动量因子的影响。中性化前后的因子表现对比如下所示："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IC</th>\n",
       "      <th>IC_IR</th>\n",
       "      <th>LongShort_sharpe</th>\n",
       "      <th>MONO_Score</th>\n",
       "      <th>Turnover</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Neu_1M</th>\n",
       "      <td>-0.049441</td>\n",
       "      <td>-0.068072</td>\n",
       "      <td>-8.622452</td>\n",
       "      <td>2.194422</td>\n",
       "      <td>0.929800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1M</th>\n",
       "      <td>-0.045512</td>\n",
       "      <td>-0.066641</td>\n",
       "      <td>-7.728916</td>\n",
       "      <td>2.012446</td>\n",
       "      <td>0.930497</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              IC     IC_IR  LongShort_sharpe  MONO_Score  Turnover\n",
       "Neu_1M -0.049441 -0.068072         -8.622452    2.194422  0.929800\n",
       "1M     -0.045512 -0.066641         -7.728916    2.012446  0.930497"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat([trans2period(Neu_far,20).iloc[0,:],\n",
    "        trans2period(basic_far,20).iloc[0,:]],axis=1).T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "提纯后的动量因子 Neu_1M 单调性改善显著，且多空夏普从8.84提升至10.15,单调性得分也有所提升。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "提纯后的多空净值为0.1353,原始因子多空收净值为0.1240\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2ddd75c7b00>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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X39KRtBhPSwcgIiIiIu2P3bKxSVaEzC6q4k9fbCYxOoKMxCgyEqMYlBrD8LTWn8BrRltEREREmpQNBGDb5ibpOPLstznklvmJMLBgaykvLNrBndM2UVIZaIJIw0sz2iIiIiLStHZsBX/1IXccWZpTxuzNJVw8MpVzhnUFYM7mYv70xRY2FFZyWLe4pog2bDSjLSIiIiJNa1fHkUNYrMa1lmcW5NA1zsMZg5NrtvftEgPAhp2VhxZjM1CiLSIiItJB2LIS7JIFWGvDe50tG8AYSM886HPM2FDMqrwKfjoylWjP7pS1a6yHC0akMKBrTFOEGlYqHRERERFp52xpMfbTd7DT3oXyMszJP8ace1n4rpe9AVLTMdHRB3V8dcDlhYU76JMczbG9O9XaZ4zh/OEpTRFm2CnRFhEREWmnbGUF9n0f9rP3g6s0HnE0JioGO/Ut3MROOKf+JDwXPsSOIx98v5Oc0mruHptJhGOaMLDmpURbREREpI2wgQBUlmPiEg48duNa3KcegO3ZmCMnYH7oxfTohXVdCPixbzyHG5+IM/Hkpo2xuhpysjGHH92o48qrXfLKqskprebVJbkc3j2eUd1bfwu//VGiLSIiItIG2LJS3H/cDdkbcW64F9N7QN3jrMV+9h729WcgvhPO9fdghoys2W8cBy67LlhO8sI/sfGJmMPHNzyOHdugohyT2afuAds3g+vWdBzxu5Zvs0tJjI4gLSGSpJgI/C58n1vOou2lfLetjA07KymtdmtOERVh+Nno1AbH1Fop0RYREZF2xwYC2Leex/Qd3KgksrWypcW4j9wFm9dDYifcv/8R56Y/YXr2rj2uuAj3uX/AojkwYgzOpddhEjvtcz7jicS5+jbch/+A+9QDOL+4BTNq3IHjyN2O++ebobIC5/YH6+wqYvfqODJ7czF/+yq7Zn9URLAUpCpgcQz06xLDsX06kRoXSdc4DylxkfToFEVSbNtPU9v+OxARERHZi536Fvbjt7CAOeYEzPlXYmJad8/l+tjiQtyH/wDbtuBccxt0z8T92224j9yJc/P9mPSewV8svpqKnfISVJRhzrsCc8IZGFN/fbOJjsH5zZ24j9yF+8T9wfE/uRQTGVl3HOVluI/dCwE/xMTi/usvOL9/CBO71+e6ZQNEREBaBgDbS6oBuGViBjvLA2wvqcK1MCwtjmFpcSRERTTNB9UKKdEWERGRFmFdN1jGcAjHY8w+yaTdsgH7zsswehymexb2w9ex3y/FufwGTL/Bhxp2s7LFhbgP3A5523F+dQfmsNEAODfci/vAbbgP/QFzzqXYD18PJrgDD8O54CpMz3rKOvZi4hNxfvdX7BvPYqe9i121DOeqmzGhJLkmDjeA+9SDsG0zzm/vhogI3IfuwH3uHzi/+F2te2CzN0JaD4wnmLDnlfmJ9Tgck7XvzHp7pz7aIiIi0uzcj9/E/e1F2O+XNOo46wawK7/DfelfuDf9DPd3l2OXLNi93+/H/e/fITYe5+JrcX78U5yb7wfXxf3brbhvvYAtLWnYtaoqsYvnBhP6FmKnvAQ52Ti/uasmyQYw3Xvi3HAPVFVi//NQsJTjl7fi3HR/g5PsmnNFRuKcfyXOtbdD7nbce6/HnfoWtrR4dxyvPQvfzcNc8AvMkJGYgcMwZ18C87/BTnsnOKaqEvez92Dld7VKSvLKquka1zHndsP+rr1e79PAUOB9n893Xz1j0oDXfT7fxND3WcDzgAusBn7h8/nC21ldREREws5ai337JewHPvB4cP/zMM5dj2LiE2uPq6rE/defYf1qiI2DmNjgn9uzobAAoqIxI8Zgt2zAffSPmGNPxZxzGfaTKbBxDc7Vt2ISOwNgBgzFufNR7CtPYj94DTvtPcyxp2BOPBOT3LXuONetwn3m77B1E+bKmzBHTQr7Z7NPDDnZ2BmfYCaeghk0fJ/9pmcfnJvvx65ZgTn6eExk1CFdz4wah3NXP9xn/4F97Rns2y9hjjgGUrphP52COeEMnMmn7R5/8o+xq1dgX38WtyAfO2s6FO2E/kMxZ1xQMy6vzK9EOxy8Xu/ZQITP5xvv9Xr/6/V6B/h8vlV7jUkGngP27N/yC+Bqn8+33Ov1fggMBxaHM1YREREJL+u6WN/T2GnvYiaejJl4Mu5fb8V97jGcq2+rKT+w1mJfeAKWLMCMPx7cALaiHMrLoP8QzBETMCOOxETHYKursG+/iP1kCnbpt1CQiznq2H1ay5m4eMzPr8eefBb2ozdDi7e8hxl7bDCJHjQc4/Fg/dXBvtMfvAadu0BcPCyaCy2RaE95GSI8mB966x1jevbe54HIQ2G6pBJxw73YTeuwX36EnfU5VJTDYaMx5/689lhjcC67DvdPN2CnvgVDRuJcdQtm0LBa4/LK/Ixs4236Dla4f72YDPhCr6cCE4BVe40JAOcBU3Zt8Pl8v99jf1cgt66Te73eq4CrQseQktI2VglqaR6PR59VK6D70DroPrQOug+tQzjvg60op+iph6n47H3ifnQ+CZf+GmMMpRf/kpJnHyd+wdfEnXIWAKXvvELJrM+Jv+BKErwNWL3w6luomnQShf+4D5K60PVXt+HU0WkDgJQUGDWGwPZsSqf8j4rpH+B+Mw2TkEjUmIn416/Cv24VMcf/gMSfX0fx049SOfcruiYnYSKaZ1bW4/HQuTif/DlfEveTS0jsP7BZrltLSgqMHoN71Y1ULZ5L1IgxOHs/9BgcSODP/4dbWEBkn33bDfpdS0HFCjJTOrW5n/Gm+HkI99+YeGBL6HU+cPjeA3w+XxGA17vvb2ter/c8YKnP58veZ2fw2CeBJ0Pf2tzcOvNx2UtKSgr6rFqe7kProPvQOug+tA7huA+2tBj72fvYz96FkmLMGedTcfoFVOblBfePPxHmfk3x03+nND0LCvNxn30cRo+jfPIPqWhoPGmZ8MfHobqK/MoqqDzAcRFRcPbPMKefj1n2LXbBTCpmfwGeSJxrf0/1qLHkl1diB43ATv+A3NlfYwYedoifRsOkpKSQ/8zjEJdAxaRTqWzpn41+h0FpWfCrPonJUEeceWXVuBbiqGpzP+P1/TxkZGTUMbpu4U60S4DY0OsEGvHwpdfr7QvcBJwYhrhEREQkjGx1NXbKi9jPPwou/T3yKJzTztmn64dxHJyf/xb3j7/B/fdfoLgQuvfE+flvG92RxERGQj2t6eo9JioaRo3DjBqH9fvBMRhnj3ZzQ0dBhAe7eE6zJdpVS78NPnj4k581aAXI1iy3zA9A19jG3Zf2ItxdR+YTLBcBGAmsb8hBobrt/wE/9/l8heEJTURERMLFvv0i9uO3MCOPwrnrH0T86o56W+uZTsk4P78etm0G6+Jc+/sW6XltPJ7aSTYEe0QPPAy7eF6zxGCtpeTFf0NSF8xxpzfLNcMpryzYQ7ujPgwZ7kT7beBir9f7MOAFlnq93jo7j+zlViALeMzr9X7u9XqPDWeQIiIi0jg2eyPuK08FH1Lce9/3S7GfvI2ZdCrOlTc26GE9M+zwYHu6G+7DdOsehogPnhkxBrZuwuZsDf/FFs+jesV3wZKW6OjwXy/M8kIz2ikdNNEO67v2+XxFXq93MnAS8Defz7cNWFTP2Ml7vP4d8LtwxiYiIiIHx1qL+8I/YfUybO52nGtuq5kJthXluM8+CilpmHMb8CDjHswRRx94UAswI8ZgX/0P9rt5mBPOqNluKyuwzz0GQ0ZiJpy031UYG8K6Ady3nieie0/sMe2jcjavzE+kY0iMbr+rP+5P2H+98Pl8BezuPCIiIiJt3ZL5sHpZsH550Rys77+Y868EwL72DORuDy6cEhN7gBO1DaZbd+ieiV08F/ZMtF/7L3buVzD3K+ySBTiXXLtPP/DGsDOnw5YNJNx0HyWe9jEDvKuH9qH+EtJWaWVIERERaTDrurhvvgCp6Ti/vhNz4pnYae/iTnsPu2QB9suPMCed1WwPDjYXM+JIWLkEWx7svGEXzcV+8RHmpDMx51wGi2bj3n1do1e63MVWVWLffgn6DCT66OOaMvQWlVfecVeFBCXaIiIi0gh27leweR3mzIuCDw+eeymMGot99T+4Tz8E3TMxZ13U0mE2OTPiKAj4YdlCbFEB7nP/gJ69MT++BOeUH+Pc+jeIjMR98A7cV/+DLS5q1PnttHdhZx7OOZe2q9nfvDJ/h+04Akq0RUREpIGs34+d8lIwwRwzEQDjROBccSNk9YXyMpzLrz/kpcBbpX6DIS4Bu2gO7rOPBd/rFTcFWwoCpvcAnD88gpl4Enbae7i3X4n73it1Piy6N1tchP3wdRh5FGbgsAOObyustR16+XVohhptERERaR/s15/Cjm04v/5DrR7XJjoG56b7ID8Xk5HVghGGj4mIwAw7IrgkuXUx51+J6VH7vZqYOMzF12JPOAP37RexU17GfvY+5rRzMJNOrbeLiP3ABxUVOGdf0gzvpPkUVwaodm2HTrQ1oy0iIiIHZCsrse++Av2HwPAj99lvYuLabZJdY8SRYF0YOhpz3A/rHWYysoi45vZgOUmPXljf08EZ7qlvYSsrao21O7Zhp3+AmXBiu/v8ahar6cCJdsd95yIiItJg9osPoDAf56qb21UNcWOY0ePgtHMwJ5zRoFUrTb/BRNx4H/b7pcEykteewX70JmbwCGxhPuTnws48iHAwP7qgGd5B88qrSbQ7bo22Em0RERHZL+u62M8/hIHD2l03kcYwUdGYgyjvMAMPI+KGe7Grl+G+78OuXQnJKZi+g4J/jhiDSeoahohbVl55cFXIjrpYDSjRFhERkQP5fgns2Ib50YUtHUmbZvoPJeK6P7Z0GM0mr8yPYyAppuOmm6rRFhERkf2yX30CsfGYw8e3dCjShuSW+UmO8RDhdMxSI1CiLSIiIvthS0uwC77BjD0WE1V314xwWbStlFV5B26PV5+8smr8rm3CiKQx8ss69mI1oERbRERE9sPO/hz81ZiJJ9Xavjqvgoe/zqbS7x70ufd37MbCSu6ZvolbPt6Ab0kugUYmzEu2l3HVlDX8/pONFFcGDjpGOXi5HbyHNijRFhERkf2wMz6BrL6YrH61tvuW5PLF+iLe/76g8ee0lv8t3sEFvu/5esO+Kyi61vLErG3EehzGZyby0qJc7p6+iYLyYBeL6oDL7E3FPDhjC4/N2kpRhb/W8VuLq/jLl5vpEuthdX4Ft07dwI7S6kbHKYcmuFhNx+04AnoYUkREROphN6yBTeswF/6y1vb8cj9zt5TgcQyvL83jpH5JJEZHNOyc1vLiolxeX5pHYpTDw99sJSnGw2FpcTVjPl61kxW55Vw3vjvH9enEqDWFPDVvO9d9sI4jMuKZvbmE0iqXxOgIyqtd5meXcv3R3RmZHk9JZYB7P98MxnDPCVnkllVz/xdb+N3HG7jzuJ70To5p0s9I6lZWHaDc72pGu6UDEBERkdbJzpgKkVGYsZNqbZ+2ZieuhZuOyaCsyuWNpXkNO5+1PL9wB68vzePk/p355xl9SU+I5E9fbmbjzkogWFf9/MIdjEiL47g+nTDGcHL/JB46tTdJ0R6+2VjCmB4J3HVcT549uz8PnNKL+EiHu6Zt4rlvc/jbjC1sL6nitok96J4YxfC0eP58UhYWuP2TjSzZXtbUH5PUoaaHdqwSbREREZFabFUldvaXmMPHY+ISara71vLJmkKGpcUxPiuRyX068d7KggOWZlQFXP67IIc3l+Vz2oAkrj4qnU4xHu48ridRjuHu6ZvIK6vmqXk5+F3LNWPTay2Mk5UUzaM/7M3L5w7g+qMzODwjAY9j6NslhodO683J/ZN4c1k+i7aVcfVR6bVmyHsnx/C3U3qRHOvh7umbWJ1XUVeI0oR2JdopHbx0RIm2iIiI7MMu+AbKSzETT661/bvtZWwvqebkfp0BuGhkKgD/W5y77zmsZWlOGU/M3sqlb67mnRUFnD4omV+MScMJJdFpCVHceVwmJVUuN3+0gZmbijlvWArdE6P2OZ8xps5WcTEeh2vGpnPHsT35zbh0TuyXtM+Y1PhI7jsxi87REdz3xWZyy1SzHU67Pt+OXjrSsd+9iIiI1AjkbMX94hPsd/Ng5WJITYeBw2qNmbp6J4lRDuNTHZNdAAAgAElEQVSzEoFgAvvDQcm8syKfM4d0ISMxiqU5ZczbUsLszSXklFYT4zGMy0zkuD6dGZket88S7n27xHDbpB7cM30TvTpHc9bQLgcV/5ieCfvdnxzr4Y7JPbl16kbu+3wzfz6pF7GR9c85FlUG+GJdIacOSCIyQnOTjZEfmtHuokRbREREOhp35nTswtlQvBOKC6G4iNzS4uDO1HTMhJMxk39QKykuqvAza1MJpw1IImqPxPMnh3Xlk9U7uXf6JoqrXCr8LpGOYUR6HBeOSGFcZuJ+E1qAUd3jefDU3iTHevCEcYGT3skx3Dwhg/u+2MxDX2dz26Qedc6Sby2u4p7pm8guriY51sOEXp3CFlN7lFvmp1N0RK2/Jx2REm0REZEOxlZXYV/+N0RFQ3pPTI/e0Kkz8X0GUNZnEKT12GfWGWD6uiL8ruWk/rVLMzpFR3DxqFTeXp7Psb07MaZHAiPS44j2NC7J6tuleTqCHNEjgSuOSOPJedv574IcLju8W63kfsWOcv70xWYs4JhgT29pnDwtVgMo0RYREel4vpsPFeU4v7wVc9joms3xKSmU5+5baw3Beuupq3cyKCWGXkn7rhB52sBkThuYHLaQm9oPByWTXVzFeysL+GZjMacNTOLU/kksySnjkW+20jXOw52TM7n38001HVFagzeW5rE0p4zbj+0Z1pn/Q5VX7u/wHUdAibaIiEiHY+fNgIROMHhEg49ZvqOczUVV/Hpcehgja15XHNGN0d3jeXdlAS8tysX3XR5+1zIoJZbfH9uDTjEespKi2VhY1dKhAvD1hiKeX7gDgA++L+BHgw+ulr0q4Ia9pCOvzM/ArrFhvUZboERbRESkA7GVFdhFczDjj8NENGyRGYAv1hcR43HaVa2yMYYjeyRwZI8ENhZW8sHKAixw+RHdahLRrM7RzNlc0izJ6f6sL6jg0ZlbGZwSS4zH8L/FuUzq1YmkBs4aW2tZvL2M15bksXxHOfeekMnQbnEHPrAOVQEXv2uJi6z7709VwKWoMkCKSkfU3k9ERKQjsYvnQVUlZszERh23ZHsZw7rFEtPIuuu2IqtzNL88Kp2rj0qvlVBndY7GtbClqOVmtYsrA9z/5RbioyL43aQeXDkmjaqAywuLdhzwWNda5m4u4XdTN3DntE1sLqykc3QEf5+5lbLqQKNjqfS7/O7jDVz9ztp6PxN1HNmtff60iIiISJ3s3C+hczIMGNrgY3ZW+NlcVMVhBzkD2pZlherRN7RQnXbAtTz4dTZ5ZX5undSDLrEeenaK5oxBXfh0TSHf55bXeVxhhZ83l+Zx9Ttrue+LzRSU+/nlmDSePKsfN07IIKekmmcW5DQqFmst/567jbUFlVS7ljunbSSnZN9+5FqsZjcl2iIiIh2ELS+D7+ZjjpyAcRpeNrIsJ7hs+Z6rLXYUGYlRRBjY1EJ12l+sL2Lh1lJ+MSaNQSm7a569w7uSHBPBk/O241oLBJPyxdtKeWhGNj9/azXPLdxB1zgPNx6Twb9+1I/TBiYTFeFwWLc4fjy0C1NXFzJvS0mDY/l49U4+W1vEecO7ct8JWZT7Xe78bCP55f5a47RYzW76BERERDoIu2g2+KsxR05o1HFLc8qJjjD0a6b2e61JZIQho1NUi81oT19bSPfESE4KrcS5S1xkBD8b3Y2/z9zK/xbnUlbt8vWGIgoqAsRHOpw6IJlTBiSR1XnfDjEAF45IYX52KY/N2spjP+xDp5j9p4Tf55bz1LwcDu8ez3nDUohwDHcdl8md0zZy17SN/OmkXnSKDv7ylhdKvJVoa0ZbRESkw7BzZ0CXFOg7qFHHLc0pY3BqbKtuJxdOWZ2j2dQCvbRzy6r5bnsZk3t3rrOv+eQ+nRiUEotvSR4fr9rJ4NRYbpmQwTNn9+fKI9PqTbIBIiMcrj+6OyVVAf45ZzsB17KjtJrF20r5ZPVOZm8upqQyWMNdVOHnr19toUushxuOyahZ4CfYnaUnW4uruePTjWSHarbzyvzEepx6H5bsSPSrhoiISAdgS0tg6beYE87AOA2fZyupDLC+oJILRqSEMbrWrVdSNF9vLKbC7zbrw6BfrivCAsf2qbvTizGGWyZmsHJHOaO6xxMf1bjEtk9yDBeOSOX5hTvwvroSv7vX+YHeydFYC4UVAf56Si8So2tfY0R6PHdM7smDM7Zww4fruXZsuhar2YM+BRERkQ7AfjsTAn7MmMaVjSzfUY6FDvkg5C67ZoY3FVYyoBl7Q3++vohBKTF0T4yqd0xKXCQpvQ7+ocOzhnShrNrFtZb0hCjSEyNJi48kt8zPkpwylm4vY01+BdeMTa+3dGhU93ge+UEfHpyRzYNfZxPpGIZ2Uw9tUKItIiLSIdi5MyA1HXr1b9RxS3PK8DiGAV07Xn32Lrs6j2zc2XyJ9vqCCjbsrOSqI9PCep0Ix3DxqNR9tqcnRjEsLQ6GN+w8qfGR/OmkLF5atIM3l+WTnlD/LwcdiRJtERGRds7uzIMVizCn/qTOWt/9WZpTxsCuMUS30/7ZDZGeEEmkY5p1hcjp64qIMDCxV2KzXfNQeRzDz0Z349jeneii5dcBPQwpIiLS7tmvp4HrYo45oVHHlVe7rMmvOOgVBNuLCMfQs3MUG+voPFIdcGva6zWVgGv5cn0Rh2ckHLAbSGvUOzmmTcYdDvoURERE2jHrutgZn8Cg4ZhuGTXbqwIu2UVV5Jf7g19lfkb2chi0x3N3K3PLCVg4TPW2ZHWOZmmon/guO8v9XPPeWlwX+iRH0zs5mj7JMYzLTKxpdXcwvt1cSH65n8vreQhS2g4l2iIiIu3Zyu8gdzvmrJ/W2nzntE0s31F7VcGXF+dy34lZwdpcgmUjjoHBqUq0s5Ki+WJ9EaVVgZruHm8sy6O82uWkfklsKqxk+toiPvDv5L2VBTxwSq+DLrf5eEUOsR6HMT0SmvItSAtQoi0iItKO2a+mQnwi5vDxNdtySqpZvqOcUwckMbl3J7rEeYiNjOC2TzbxyDfZPPqDPiRER7Asp4x+XWLUDxnI6hx8uG9TYRWDU2PJK6vmo1U7mdynM9eMTQfAtZbZm0v4y5dbeHp+Ts32xqj0u0xfncfRWYkdui6+vdAdFBERaadscRH225mYcZMxkbu7QMzaXAwEW7sN6RZHWkIUnaIj+OOpgygo9/OvuduoDriszK3o0G399tRrV+eR0MI1byzLx+9azhvWtWaMYwzjMxM5e2gXPl69kxkbihp9ndmbSyivDjBZZSPtgma0RURE2ik7azr4/ZiJJ9faPnNjMb2SovfpzzwkPZHzR6Tw0qJc4iMjqHat+iGHpMZHEh1h2Lizktyyaj5etZMT+nYmvY4e1xeNTGVpThlPzN5Gvy7774O9p7LqAFOW59MtIaqmfEfaNs1oi4iItEPW2mDZSN9BmB69arbvLPezfEc54zPrrv/9ydCuDE2N5ePVOwEYmqqED4Kz1VlJ0WworOT1JXlYazl3j9nsPXkcw03H9MAYeGBGNtUBt85xeyqs8HPHp5tYW1DBryb2wWlkG0ZpnZRoi4iItEdrVsDWTZgJJ9XaPGdLCRYYn1l3f+YIx3D90RnERTr0SoreZ8ntjiyzczSr8yr4ZM1OTuyXRNp+FmXplhDJb8Z1Z01+Bde+t45nFuSwYkd5na0Ac0qquXXqRjYVVnL7pJ6cMHDfBWSkbVLpiIiISDtkZ0yF6FjMmIm1ts/cWEx6QmRNzXFduiVEcu8JWTiaVK2lV1IUn6118Tim3tnsPY3LTOSWiRlMW1PIeyvzeXt5PsmxHoamxpIUE0GnaA/xUQ5vLcunIuBy9/GZHb5neXujRFtERKSdsYUF2LlfYcZOxsTsrrEurQqweHsppw/qcsAVIvt34CXX65PVOfjLycn9O5MaH9mgY47J6sQxWZ0orQowb0sJMzeVsK6ggqLKACVVwZKSLrEe7j8xi97J+szbGyXaIiIi7Yx97xUIBDCnnF1r+7wtJfjd+stGZP+GpcVx7mFd+dHg5EYfGx8VwbF9OnNsn8412/yupaQyQFyUQ1SEqnnbIyXaIiIi7YjdtgX75ceYSadi0jJq7Zu5qYTkWA8DUzRzejCiIhx+Oqrp6qc9jiEpVqlYe6Zfn0RERNoR960XIDIac8Z5tbZX+l0WZJcwrmeCOlqINBMl2iIiIu2EXbMCFnyDOfksTKfa5Q3fbi2lMmAZp7IRkWajRFtERKQdsNbivvEsdErCnHzWPvtnbSomIcrRQigizUiJtoiISHuweC6sWoY54/xanUYAdpRWM3tzCWN6JOBRzz6RZqNEW0REpI2zrov75vOQ1gMzofZy69UBywMztuBaOKcBvZ9FpOmE/VFXr9f7NDAUeN/n891Xz5g04HWfzzcx9H0k8CbQBXja5/P9N9xxioiItFlrV0D2Rsxl12E8tf9pf/bbHFbmVnDLxAx6dqp/kRoRaXphndH2er1nAxE+n2880Nfr9Q6oY0wy8BwQv8fmXwPzfT7fMcA5Xq9XT26IiIjUw87+EqKiMIePr7X9q/VFvLeygDMGJ3NMVqcWik6k4wr3jPZkwBd6PRWYAKzaa0wAOA+Ystdxt4ZefwkcCUzf++Rer/cq4CoAn89HSkpKE4Xdvnk8Hn1WrYDuQ+ug+9A66D4cPBvws2PBN0SPmUhSz6ya7Rvyy3hiziqGd0/kphOH4GnAgii6D62D7kPr0BT3IdyJdjywJfQ6Hzh87wE+n68IwOv17u+4tLpO7vP5ngSeDH1rc3NzDz3iDiAlJQV9Vi1P96F10H1oHXQf9s+WlmBnfY6ZfBomIqL2viULsEU7qR45tuYzrA643PrheqIcuH5cN3YW5DfoOroPrYPuQ+tQ333IyMioY3Tdwv0wZAmw69HnhEZc72CPExERaXfsB69hX3kS+9XUfffN+QJi42HYETXb3lqWz8bCKq4b352ucZHNGaqI7CHcCex8guUiACOB9WE+TkREpF2xFeU1CbZ993/YivLd+6oqsd/Owhw+HhMZTKi3FVfx2tI8jslK5IgeCS0Ss4gEhTvRfhu42Ov1Pgx4gaVer7fOziN7eQ642+v1PkqwY8nsMMYoIiLSatmvp0F5Kea8y6FoJ/bTd3bv/G4+VJRjjpoUHGstT87bjmMMlx/RrYUiFpFdwppoh+qvJwOzgON8Pt8in893Rz1jJ+/xegNwEvA1cKLP5wuEM04REZHWyLoB7LR3oN9gnBPPhFHjsB+/iS0uAsCd8wV0SoLBwwGYtbmE+dmlXDgiRSUjIq1A2Pto+3y+AnZ3HmnMcdkHc5yIiEi7sWgu7NiGc/YlADhnX4x71xzsBz444wJYPA9z7KkYJ4Lyapen5m2nd1I0pw9KbuHARQSaIdEWERGRg+N+OgW6doPRwf7YpnsmZsKJ2OkfQGwc+KsxYyYC8Op3ueSV+bl5QgYRWmZdpFVQNw8REZFWyG5YDd8vxRx/eq2WfuaMC8BxsO++Ailp0HcQJVUB3lmRzwl9OzMkNa4FoxaRPSnRFhERaYXsJ1MgOhYz4aRa201yV8yJZwRfHzUJYwzfbSsjYOGEfp1bIlQRqYdKR0RERFoZW5CHnTcDc9wPMXHx++w3p54DpSWYyT8AYNG2UmI8DoNSYvcZKyItR4m2iIhIK2O/+BBcizn+9Dr3m7h4zMXX1ny/cFspw9Ni8ag2W6RVUemIiIhIK2NXfgf9BmFS0w84dntJFVuLqxmZvu/Mt4i0LCXaIiIirYh1A7BpHaZX/waNX7StDICR3ZVoi7Q2SrRFRERak5ytUFkBmX0bNHzh1lK6xHrI7BQV5sBEpLGUaIuIiLQidsMaAEyvAyfarrUs3l7GyPQ4jFF9tkhro0RbRESkNdm0FjyRkJ55wKHrCioprgwwSmUjIq2SEm0REZFWxG5cCz16YTwHbgy2cGspgB6EFGmllGiLiIi0EtZa2LAGk9V3n+1biqr2Gb9oWym9OkeTHKtuvSKtkRJtERGR1iJ/B5SVQFa/WpvfWJbPNe+uZcry/JptlX6XZTnljOyuJddFWisl2iIiIq3Frgch95jRziur5rUlucR4HP67IIfP1hYCsHxHOdWuZZTKRkRaLSXaIiIirYTdtBYcB3r2rtn2wsId+F148NRejEiP47FZW5mzuZhF20rxOHBYmma0RVorJdoiIiKthN2wBtJ7YqKiAViZW870dUWcNaQLmZ2juW1SD/omx/DAjGy+WFfE4JRYYjz6p1yktdJPp4iISGuxaS0mVJ/tWstT87aTHOvhJ4d1ASAuMoI7j+tJanwkeeV+rQYp0sop0RYREWkFbFEB7MyHUH325+uKWJVXwSWjUomLjKgZ1znGw93HZ3J8304c37dzS4UrIg2gRFtEROQQue++QuDRu4Pt+RrAlhZjN6yuvXHjWgBMVj/KqgM8v3AHA7rGMLlPp32OT42P5LrxGaTERR5y7CISPkq0RUREDoF1XewXH8GS+bBoToPGu4/di3v/Tdg1K3ZvD3UcIbMP7ywvoKDcz5VHpuFoaXWRNkuJtoiIdCh24xoCD/8B96upWDdw6CfcsBoK88FxcN/93wFnte3Mz2DNCvBE4j79MLaiLLh901pITcfExbN0RxkDusYwKCX20OMTkRajRFtERDoM+9183L/dDquWYZ9/HPf+m7Grlx/aORfOBsfBnHNZsPxj4ez6x5YWY19/FvoNxrnuLsjNwb7yn+DOjWtr6rO3FlWRkRh1SHGJSMtToi0iIm2Kzd6Inf8NNmdrg2uiAdwvP8J9/F5I645z/5OYK26EwgLcv/4O9+lHsKUlBxfPojkw4DDM8adDtwzcd/6Hdd26x771ApSW4Fx0NWbgMMxp52C//hT3q6mwYxsmqx9VAZfcMr8SbZF2wNPSAYiIiByIdQOwaC7uZ+/BisW7d8QnQq/+mD4DML0HQO8BmKQuexznQtFO7GfvYj98A4YdgfOLWzAxsZixx2JHHoX98HXsx29h1yzHufo2TGafhse1Yxts2YA573JMRATmjPOwTz8CC2fB4UfXHrtuFfbLjzHHn15zDXPG+dhl32Jf/Gfw+6y+bCupxgLpiXrQUaStU6ItIiKtmjvrc+zbL0JeDnRJxZz9M8ygYdjN62D96mAC++Hru2eRk7pC19Rgq7yd+RDwA2AmnYq58BeYiN2t8kxMLObHF2NHjMH9919w/3Iz5uJrccYd16DY7KJgmYgZOTb451GTsO/7cN/5H86ocRgn+D+OrRvAfelf0CkJ86MLd1/f48G5/Abce38LVZWQ1ZetRVUAmtEWaQeUaIuISKvlfvkx9oUnoM9AHO/PYeTYmkTZ9B0Ek4LjbGUlbFqLXf89rFuN3ZmH6TcEuqRAlxRMek8YPAJTTwcP028wzh8ewf2/B7BPP4K7diXmzJ9i4hP2G59dOAd69MKkpgfP40RgTj8f+5+HsPNmwMBhUFyI/XYWbFiNueJGTFztRWZMeg+cy67Dfjcf0ymZrVvyACXaIu2BEm0REWmV3K+nBUsqhh2Bc83tmMj6SylMdDT0H4LpP+Sgr2c6JeNcfw/2zeewn0zBTv8AOneBjExM90zMhJNqlZXY0mJYtRRz6k9qn2fMBOz7PuxTD1KrgnzISMxRk+q+9pETMEdOAGBrcTWJUQ4J0RF1jhWRtkOJtoiItDrurOnY5/4BQ0biXHPbfpPspmQ8Hoz3cuzh44M9rrM3Ybduws74BDv/G5x7nqiZkbbfzQPXxYwaW/scTgTO5TdgF8+FxE6YxCRI7Ax9BtY7o76n7OIqums2W6RdUKItIiJhYwMB7EdvQGEB9BscnHHukrrfhNMumIn976MwcBjONb/HRDZ/0mn6D8X0H7o7pnWrcP98M/at5zEXXR3ctnB2cMa7V/99j+/VD9Or30Fde1txFUNS4w4ucBFpVZRoi4hIWNjSYtz/+xssXwRRUTD9/WApRVIXjPdynDET9z2mohz35X9DVl+cX/8hWBLSCpg+AzAnnI799B3s2MnB5HrJt5ixk2oeeGwKVQGXHaV+TuirGW2R9kCJtoiINDm7dRPu4/dB/g7Mpb/BjDsOtqzHrlmBnfEp9rnHsX0GYlLSah839W0oLAi22YuOaaHo62bOvAi7YCbuC0/gnH0JVJbvUzZyqNTaT6R90YI1IiLSpOyS+bh/vhnKy3Bu/BPOMScGe0xn9cM57oc419wOBtznH6+14IzdmY/9+E044mhMv8Et+A7qZmJicS78JWRvxH3uMYiOgcEjmvQaW4vV2k+kPVGiLSIiTcbm78B94k+Qkobz+4fr7AJiuqZizr0Mli/Cfvnx7mPfeRkCgeBscRiVVAZ45OtsvlxfhNuIlSUBzMgxmCOOgeJCOGx0k9eP70q09TCkSPugRFtERJqM/fgtsBbn2jswXVPrHWcmngJDRmJfewabl4N/41rsjE8xk0/DdMsIa4xTVuTz+foiHvo6m5s+2sDibaWNOt6cfyV0z8Q55sQmj21Xa79EtfYTaReUaIuISJOwRQXYr6Zixh233yQbwBiDc8mvAIv73GMUP/9PiInFnH5eWGMsqQrw3soCxmUmcN347hRW+PnDtE3cM30TZdWBBp3DJHUh4p4nMCPGNHl8au0n0r4o0RYRkSZhp04Bvx9z2jkNGm9S0jDnXArLF1E1/xvMD87BJHQKa4wffF9AWbXLecNSOL5vZ/71o778bFQq87NLeW9FQViv3RDblGiLtCtKtEVE5JDZ0mLs5x9ijjwGk9bw0g8z6VQYOpqI7j0xJ5wRxgihvNrlnRUFHJkRT98uwY4mUREOZx/WlTE94pmyIr/Bs9rhsKu1nx6EFGk/lGiLiEijWH/1vtumvRdsd/eDcxt1LuM4ONfdSddHng/7wjQfrSqguDKAd3jKPvvOG55CSZXL+ytbblZ7u1r7ibQ7SrRFRKTB7JYNuL8+D/fJB7A784PbKsqw096FUWMxPXs3+pzGiQh7z+xKv8vby/MZmR7HoJTYffYP6BrLkRnxTFnecrPa2WrtJ9LuKNEWEZEGs19NBWux387CvfMa3OnvY6d/AGUlOD/wtnR49fp0TSE7KwJ4h+07m73L+SNSKK5y+WDlzmaMbLdtxcH/U6AabZH2Q4m2iIg0iPX7sXO+hJFjcf74GPQegH35/7BvPg9DR2H6DGjpEOtUHbC8sSyPoamxHNZt39nsXQZ0jeWIjHjeXpFPebXbjBEGZRdXqbWfSDujRFtERBpm6QIoLsQ5+nhMWgbO9fdgrrgRevXH+fHFLR1dnaoDlsdnbyWvzM+5w7pijNnv+POGp1BcGeCD75u/VntrcRXpms0WaVc8LR2AiIi0De43n0FiZzjscCDYC9uMPRbGHtvCkdWtpCrAX77cwnfby7hgeAqju8cf8JhBKbGM7h7P28vz+cHAZGIjm28+amtxFUNS45rteiISfprRFhGRA7KlxbB4DuaoSRhPy83RWGv5eNVO/vrVFt5YmseynDKqAvuWeWwvqeLWqRtYvqOM68Z35/wRKQeczd7l/OEpFFUGeGFhDraRS7QfrGq19hNplzSjLSIiB2TnfBVcjObo41sshgq/yxOzt/Hl+iKSYiL4ZmMxAB7HkNk5isToCOIjI0iIcpi7pYTqgOWu4zIZkX7gmew9DU6N5fRByby3soDICIdLR6ceMEnfWFhJYYWf4WmNu9Yu29TaT6RdUqItIiIHZGd+Bj16QWbfFrn+lqIq/vrlFjYWVnLRiBTOGdaV4soAK3aUs3xHORsLKympcskvq6S02iUpxsONEzLI6hx9UNe74ohuuNby9vJ8rLVcdni3/Sbbz8zPYWVuOS+cM4AIp2Ez53vaqtZ+Iu2SEm0REdkvu20zrPsec+5lDS6/aErzt5Tw4NfZRDiGu47PrKm17hzjYWxmImMzE5v8msYYrjoyDQNMCS3NXl+y7VrLyrxySqtdvs8rP6g6661q7SfSLinRFhGR/bLffAbGwRzV/A89llQFeGTmVrrFR3LH5J6kxjdfaYUx/8/efcfJVdX/H3+dmdles7vJJpvdLOmk9wYJhNCLKO2CoiiKCPaKWFAQ+IIoKvKzBQQREbmK9CItoQZI771uNtt7L3PP74/ZhIQt2SQ72ZL38/HII7Nzz73zmbnZ5JOzn/M5hi9PTwdCyXZydIBLx6W2GrevspGaxlCd+Mq8mqNKtFfsq6Z/bECt/UT6mLAn2o7j/BUYC7zguu4dnRnjOE4/4DFgALDcdd2vhDtOERFpzXpB7PuLYdwUTHLKcX/9J9eXUN0Q5BcLso5rkr3f/mR7R1kDb++ubDPR3lxcB0BytJ+V+2r4zMT+R/Qa+yobWZVfy9UT299MR0R6p7B2HXEc51LA77ruHGCY4zitdjNoZ8zngMdc150OJDiOMz2ccYqISDs2r4Oy4mNaBLmluI5XtpXz7p5KVufXsL20Hq8T3TwKq5t4blMZ84cmMiwlvFu0d8QYw7gBsewqb6ChuXWHky0l9cRG+DhnRDLbSuupajiyLdz/t60cv4GzRyR3Vcgi0kOEe0Z7PuC2PH4FmAts7cSYEmC84zjJQBaQE+Y4RUTkY2xtNd5//w4xcZhJM4/qGqvza7jtjRyCH8urFwxL5FtzMjo897HVRRgDV086shnicBiVFo1nYUdpPWMGHFoasrm4jlGp0UzLiMddV8Lq/BrmZid26roNzR6vbS9ndlYC/WJUzSnS14T7uzoOyG15XApM7eSYx4ELgW8CG1ueb8VxnOuB6wFc1yUtTT9264xAIKDPqgfQfegZ+tJ9sNZS97+naVy7nIRrv4k/bcBRX8urqqTsl7/A27uTpO/fTnTG4CO+xvbiGn759layU2K588IxNAU9qhqaeW1zEU+tzeeTk4YwfUhoFvfj92FTQTWLd1Xy2emZjMkedNTvo6vMjkmEN3PJrfcz76A465qC7C7fxDUzspg9OpOEN/eysd9JWSwAACAASURBVDTIp6Z17s/UixsKqG70uHJ6Nmlp3T+j3Ze+H3oz3YeeoSvuQ7gT7WogpuVxPG2XqrQ15ufADa7rVjqO813gWmDhx090XXfhQc/b4uLiLgy970pLS0OfVffTfegZ+sp9sFWVeI/8HlZ/CMZHw5pl+K7/AWbMpKO71m9vgbwcfDf8iOrh46g+ws+ouLaJm17eTZTf8ON5g4gN1gCQFAWfHpvIkp0l/PK1zdx34VAi/b5D7oO1lt8tyiExys8FQ2N6zP3pHxtg5Z5izhryUcvAdQW1eBayYi3lpSVMSI/lvZ0lFBUld6pDy79X5JCZGMmQ6KYe8T77yvdDb6f70DO0dx8yMjr+adzBwr0z5HJCpSAAk4BdnRzTD5jgOI4fmAUcn625RER6IbthFd5t34T1KzBXXofvtvshIQnvtz/He8HFeq3ritu8jrXYnVvx7v0J5Ofi+9pPMZNmHHE8tU1Bbl+0l9omj5+d0bpTSFTAx1dmpLOvqon/bmj9A8sP91aztqCWqyakERfZc7pwjEqLYUtx/SHP7V8IOSotNF80ZVAcpXXN7KloPOz1tpfWs6WknvNGdi4pF5HeJ9wz2k8DbzuOkwGcD1zlOM4druv+tIMxs4FtwMNANrCEUCmJiIgcxHoe9tl/Yl9wYVAWvm/9HJM1FADfj3+NffQP2Kf/gd2wCt8nr8aMGtf2dYoLsO8vxn6wGPJzISoG3zduObrZcGv59Tv72FPRwM/OyGJov7YXMU7NiGdudgL/WVfCadmJ7P/p7Bs7KvjjB/lkJUVy7sjuL6U42MjUaN7dU0V5fTPJ0aF/PjcX15GREEFiS1u+/T2+V+ZVk53c8WY5L20pI8pvOGNYUngDF5FuE9ZEu6X0Yz5wNnCP67r5wOrDjKkAPgTa/hdBRESwjQ3Yh36HXf4u5tSzMJ/+Cibqo8TORMfAdd+D0eOxTz+G96sfwegJ+C66EgZkwM4t2J2bsds2wvZNoZNGjceccwlm2imY2Pijiquoppnl+2q4emLagaSzPV+cOoAV+2r4y9J87sseyIPLC3huUxnj02O5aW4GgaPYYTGc9s9aby2uZ0ZmPNZathTXMemg99k/LoLMxEhW7qvhU2NatwLcr6YxyFu7Kpl3UiLxPWjWXkS6VtiXOLuuW8ZHXUWOeoyIiITYynK8P9wZ2q3x8msx53yqzdIDYwzmtPOws87Avv0/7Mv/xbv3oB8oBgKQNQzzqc9iZs/HpB794sn9NhTVAjAj8/CJempsBJ+d1J+Fywq45rGV7C6r4xOj+/GFqQN6XJINMDwlGp+BLSV1zMiMp6immbL6IKPTYg4ZNyUjjpe3lNPQ7BEVaLtC86Ut5TQELeeP7Hc8QheRbqJeQiIivYjNy8G77zaoKsd3ww8xU0857DkmKgpz1sXY088LbT7T2IgZNgoyh2IiunYTmA2FdcRG+BiS1HHZxH7njUzmjR0V7Kmo55uzB3Lm8J5VLnKw6ICP7OQotrTUZe+vz/54oj11UBzPbSpjfWEtUzNa/4fjvT2VPLamiBmD4xmR2n39wUUk/JRoi4j0It5f7oGmRnzfvwsztNUeYB0yEZGYeeeEKbKQjUW1nJwWg7+TM9J+n+G2BVlEJyQRaKwOa2xdYVRqDO/sqcSzls0ldUT6Tata7HEDYon0G1bk1bRKtNfk13Dvu3mMTI3h+3M737lARHqncHcdERGRLmKL8iF3N+b8y484yT4eKhuC7KloZOyAmMMPPkh8lJ+Bib1jZndkajQ1jR77qhrZUlzPiJToVmUuUQEfYwfEsnhnJa9uK6fZCzXO2lpSx51v5pKREMEt8zOJbqesRET6Dn2Xi4j0EnbdCgDM+GndHEnbNrXUZ4/tH3uYkb3X/gWRGwrr2FFaf+Drj7t2Sn8Gxkfw/z7I58Znd/D0xhJ+sWgviVF+bl2QRUKUFkCKnAiUaIuI9BJ23XLoPxDSe2bJwcaiOgI+w8i03jE7fTQyEyOJDvj439ZymjzL6Hbe60n9ovnVudncMj+TxCg/D68IbSd/24IsUmO7ti5eRHou1WiLiPQCtqkRNq3BnHpmj93cZH1hHSNSoon09905HL/PMCI1mnUFodn7jy+EPJgxhumD45mWEcfaglr6x0UwKCHyeIUqIj1A3/3bUESkL9m6HhobemzZSEOzx/bSuiOuz+6NRrV0CkmNDXRqdtoYw8SBcUqyRU5ASrRFRHoBu3YFBCJg9MRDni+obmR3eUM3RfWRrSX1NHt9uz57v/112R3NZouIgEpHRER6BbtueWjnxoN2f3xvTyX3LcnD7zM8+KnhxEZ03wK7/RvVnNy/7yefo9Ni8BkYdwLM3ovIsdGMtohID2eLCyB/L2bCVACCnuXRVUX88u19pMdFUtPo8fKW8m6NcWNhHdlJUSdEN42UmAD3XTiU87Sro4gchhJtEZEezq5bDoTa+lU3BLlj8V7+s76Ec0Ykce/52UweGMszm0ppDHrdEl/Qs2wqrmPMCTTDOyQpqkduEy8iPYsSbRGRHsLu3kbw/76P3bDy0OfXLoe0dEgfzF1v57KmoIavzhzI12YNIsLv47JxqZTXB3l9e0W3xL27vIHaJo8xJ0DZiIjIkVCiLSLSA9iGBrwH7oWdW/Duuw3vrZdDz+9v6zd+GhUNQdYV1HLF+DTOHZl84NwJ6bGMSo3mqY2lBFt2ITyeNhbVAaGtx0VE5CNKtEVEegD75MNQkIvvqz+GsVOwj/4R798PweZ1B9r6rcqrAWB6Rvwh5xpjuHx8KgXVTby9u/K4x76+sJa02AD947QRi4jIwdR1RESkm9l1y7GLXsScdTFmymx8E2dgn3gQ+8rT2HdehUAATp7AymWlJEX5GZYS1eoaMwbHMyQpkv+uL+W0kxLxHadNbay1bCyqY3y6ZrNFRD5OM9oiIt3IVlfi/e1+GJSFufQaAIzfj+8zX8FcdT3U1cHoCdjIKFbm1TBlUFybSbTPGC4bl8ruigaW5lYfl9jL65v56/JCSuuaGav6bBGRVjSjLSLSjexjf4bqSnzfvAUTcejOgb4zL8KOGgfxiWwrraeiIciUjLh2rzUvO5HHVhfz5PoSZg6OD9tW7VUNQZ7aUMLzm8to8ixnDktiwbCksLyWiEhvdlSJtuM4fuAy13XdLo5HROSEYbduwC57B/PJqzFDhrc5xmQNBWDl2mIMMGVQ+4m232e4dGwKf15awMq8GqZ+rJa7KxTVNPHtF3dS0+gx76RErpqQxuBEbS0uItKWDhNtx3GeBH4ETHFd9wnHccYB1wE/AL4GKNEWETlK3nOPQ2Iy5uxPffSctW2WhqzIq2F4SjRJ0R3Pj5w1PJn/bijlH6uLmTIorstntV/fUUFNo8evzstmZKrKRUREOnK4Gu3+hJLxWxzHmQP8CXjcdd1moHt2RhAR6QPsto2wcTXm3EsObKu+qaiOa/+7jTX5NYeMrW4Isrm4jqkdlI3sF+E3XDUhle2l9by/t2trta21LN5Zwfj0WCXZIiKdcLhEu9l13Q3Ap4AG4GbgcsdxtIhSROQYeM/9CxKSMKeff+C5JzeUUF4f5Hfv5VHdEDzw/OqCGjwLUzsoGznY/KFJZCRE8s/VRV3aV3tLST15VU3MH5rYZdcUEenLDpswO44TDdwObAR+C2QBBjj+uyKIiPQBdvsm2LCyZTY7GoC8qkaW7q1mdlY85fXN/PHDfKwN/TW7Yl8NcRE+RqV1bhbZ7zN8emIaeyoaeXdPVbvj6po8/rOuhGc2lrImv4bK+uYOr7toRwWRfsMpQxI6+U5FRE5s7Rb7OY5zNTAaCALvAU8Qmtn+G/AVYLDjOF8FIlzXvS/8oYqI9A3e8/+C+ETM/AsOPPfC5jL8Prh+ejojU2J4dHURM3ZWMn9oIiv31TBpUBx+X+frredmJ/Cf9VE8vqaIU4cktDo3p6KBX76dS05F4yHPp8QEGJ8ey9dnDSQq8NFcTFPQ8s7uSmZmxhMb4T/Kdy4icmLpaFXNcKAOeBX4MXA18DMgERgERLX8rq3AREQ6ye7cAutWYC79/IHZ7NqmIK9tr+DUIYmkxkZwydgUlu+r5i9LC4iP9FNS19zpspH9fMZw9cQ0/u+tXJ7aUMqC4Un0i/ZjjOGtXZX84YM8ovw+fnFmFtnJUewqa2BXeT3bSxp4a1cl2UlRXD4+9cD1VuRVU9XoccZQtfETEemsdhNt13V/4TjOGcD1wO+ASOB94BTXdW9xHGeu67q3HKc4RUR6POt54HmYQPtzGN5z/4L4BMwZH81mv769grpmj0+c3A8IlX58+5RBfPvFXdzzTi5Ah/2z2zMzM54x/UOz44+uLiIu0seAuAh2ljUwpn8MP5ibQWpsaK5k8qAAk1uS+bpmjyc3lHDOyGQSo0Kz14t3VpIU5T8wRkREDu9wfbSt67pbHcf5OjAP2AT8KvxhiYj0bLa5CfvYn7G7tkJtDdTVQn0t+PwweSa+U8+GcZMxPj+2uhK77B3sB2/Cto2YSz6HiQ7VWwc9y/Obyzg5LeaQTh7p8ZF8ZUY6v30vj+ykKNJij/yHh8YYbluQxcaiOvZWNpBT0cjeykauGJfKVRPTCLRTivK5yf359os7eXJ9CddOHUB1Y5Cle6s5d2Ryu+eIiEhrh0u0fY7jDACeJFSXfRWwoeWYFkOKyAnL/usB7DuvwoTpmKxhEBsHMXFQW4398C285e9BcgpkZMPmNRAMtmyz/nnM2RcfuM6yfdXkVzfxucn9W73G6SclklvZSFZS1FHHGRXwMXlQ3BHNRGcnRzF/aBLPby7jwlH9WJVfQ5Nn1W1EROQIHS7R3gbEAr9xXXep4zibgLdaNrKJDnt0IiI9kPfWy9g3X8aceym+y7/Q6ri94lpYsxTvndegIBdz5sWYWadD1tBWG8g8t6mMtNgAc7Jad/IwxnD1pNYJ+PHwmYlpvL2rksfXFpFf1cTgxEhGpOivfRGRI9Fhou267nUtD3e1fF3lOM40Qu397g5vaCIiPY/dthH7z4Uwbgrm0s+1OcYEImDqKfinntLhtQqqG1lbUMtnJ6UdUUeR46F/XAQXju7HMxtLscDVk9K6fJdJEZG+rjN9tA8pDHRd13NdN+i67rMtx+8MV3AiIj2JLSvB+/PdkJKG78s/wPiOrc3d+zmhnRvnZvfMkozLx6USGxH6Z+L0k3pmjCIiPdnhSkcA1gGjHcdJBf4LnO267sGNV68CfhKO4EREegJrLaz+AO/xB6C+Dt93bsfExR/zdZfkVDG0XxSDEiK7IMqulxDl5/oZ6ewpbyA9vmfGKCLSk3Um0a5p+f0GoBx41HGc0YBHqIRETVVFpM+yhXl4/3oA1i6DjCH4rv8BZvCQY75uaV0zm4rquGpiWhdEGT7z1TdbROSodbQz5B3Aw0Cz4zgB4EbgvJbnZhJKsgFWhjtIEZHu4L3xPPbfD4M/gHG+hDnjwg57ZB+JD3KqsNDmIkgREekbOvoXoxl4hdBOkGcB613XXec4DsBPW8aYluMiIn2KXb0U+/hCmDAd3zVfwySnHv6kI/B+ThUZCREMSVJJhohIX9XuYkjXdW8FRgJ7Xdd9GbjioMPvAO+2/N4QzgBFRI43W7gP76+/gSHD8N3wwy5PsqsbgqwtqGV2VoI6eYiI9GEddh1xXdcDmlq+DB50qBwoa/ldG9eISJ9hG+rx/ngX+Hz4bvwRJrLtzWI8a7n1jRx+9voeXthcRnFtU5vj2rI0t5qgVdmIiEhf11GN9qXAZwHjOM4FwHeAs1sOf5aParRjwxqhiMhxYq3FPnI/7MvB9+2fY9LS2x27Yl8NK/NqSIkJsDq/gIXLChiREs2p2QlcfHJKh1uVL8mpIjU2wIhUbQAjItKXdTSjfRHw+5bHi4BEx3GuITSD/W3gWy2/l4c1QhGR48S+8QJ26duYSz6LGTulw7EvbimjX7SfhZ8czh8uGso1k/vjM/DIyiLuenMvDc1em+fVN3uszKthdlYCPpWNiIj0aR3VaH/Rdd3FQMB13TrgSuB2QiUkq4FVLb/an/IREeklbHkJ9qlHYfw0zHmXdTg2v6qRFftqOGdkMhF+Q2ZSFJeNS+VX553EjTPTWZFXwy2v51DVEGx17op91TQGLXOyjr0Pt4iI9GyH3RkSSABwXXcX8P+A11zXneC67kTXdScQqtUWEenV7JN/h2ATvk9/+bALFF/aWo4xcO6I5FbHzhvZj5vmDmZ7aT0/enV3q9rtJTnVJEb5GdtfVXciIn1dZxrC3n/Q4/sItf0DwHGcaEJ9tUVEei27bSP2/UWY8y/HDMjocGxDs8fr28uZlZlAamxEm2PmDEng55GZ/N+buXztuZ0MToxkQFwE6fERLMut5pQhCfg7qOEWEZG+oTOJ9pcJJdh8bOt1CLX8+yRwZxfHJSJyXNhgEO/xhZCcirngisOOf2d3JVWNHheMaj2bfbCJA+O4+5whvLy1nMKaJnIqGljeUjZy+knafkBE5ETQmUTb5zjOdmAfsAJ4DXgJiAN+TGhrdhGRXqnu9edhz3bMdd/DRMccdvyLW8rJSopkQvrhSz9O6hfNDTMHHvjaWktD0BId6EzVnoiI9HadSbRrgHFABjAFuBD4DVAP3O267pvhC09EJHxsTTXVj/0FRozFzDztsOO3FNexrbSe66enH9VGM8YYogMqGREROVG0mWg7jhMgNGv9J8C4rmsdx4kA0oBhhDaxiSE0qy0i0ivZ5x7HVlfi+9atHSbO1lpW59fy91VFRAd8nDFMpR8iInJ47f38MgA8AVwHjHcc50fAC8DJwM9d1x0LLABuchzn9OMSqYhIF7L1tdg3XyZ6wYWYIcPaHBP0LG/tquS7L+3i52/kUFrbxI0z04mN8B/naEVEpDdqM9F2Xbfedd0HXde9ABgNZAJ+4GnXdd9vGbMH+Arwt5YZcBGRXsOuXQHNTcTMP6/t49Zy++K93PvuPhqClq/PGsgDnxrO/KFJxzlSERHprTragn0M0NDy5b3Ai0CE4zgHT/1sBf7qum7zx88XEenRVi6BhCQiTp4IZa23A1i0s5KVeTVcM7k/l4xN0S6OIiJyxDqaif49oQWPHzcYMMDelt/bbiTbwnGcvwJjgRdc173jSMY4jvNH4CXXdZ/r6DVERI6EbWrCrl2GmT4X429dBlLZEOThFYWMTotRki0iIket3UTbdd2z23recZxTAcd13W8d7uKO41wK+F3XneM4zkOO44x0XXdrZ8Y4jjMPGKgkW0S63OY1UF+HmTy7zcOPrCykujHIV2emK8kWEZGj1mFtteM4pwC/4qMSEoBoINNxnG+7rmsPc/35gNvy+BVgLqFykw7HOI6zC3gAeNFxnE+6rvvMYV5HRKTT7Mr3ISoGxk5qdWxDYS2vba/gkjEpnNQvuhuiExGRvuJwixjXAF8i1M5vv0hgeievHwfktjwuBaZ2csw1wAbgHuAbjuMMcV33/o+f6DjO9cD1AK7rkpaW1smwTmyBQECfVQ+g+9A9rOdRvGYpkdPmkDwo45D70BT0WPjyHgYmRPG1M0YTo+4ix42+H3oG3YeeQfehZ+iK+9Bhou26bjWwqY1DGzt5/WpC/bYB4mm7y0lbY6YAC13XzXcc5x+EtnhvlWi7rrsQWNjypS0uLu5kWCe2tLQ09Fl1P92H7mG3bcQrL6Vx7BSKi4sPuQ9Pri9hZ0ktPz09k5qKMmq6OdYTib4fegbdh55B96FnaO8+ZGRkdPoa4d4HeDmhchGAScCuTo7ZRmhjHAjNnu8OW4QickKxK98HfwAz4dAfzBXXNvHE2mJmZcYzIzO+m6ITEZG+JNz9r58G3nYcJwM4H7jKcZw7XNf9aQdjZgMe8JDjOFcR6mpyeZjjFJETgLUWu3IJnDwBE3voxrZ/W1GIBb40bUD3BCciIn1OWBNt13UrHceZD5wN3OO6bj6w+jBjKloOXRHO2ETkBLRvDxTlY8655JCn1xXU8vbuKq6akEp6fGQ3BSciIn1N2Hd0dF23jI+6ihz1GBGRY2VXLgHATJ514Llmz7JwWQED4gJcOja1u0ITEZE+SFuni0ifY5saoaQQiguwFeVQXQFVFdilb8Ow0ZjklANjn16bx+7yBm6eN5ioQLiXrYiIyIlEibaI9Am2qhLv4d9Bzg4oL209IBABCUmYBRcdeKqivpkHl+xm0sBYZmdpAaSIiHQtJdoi0utZa/H+8QfYsAoz63RIS4f+6ZjUdEhOgYREiIrBfGyXx3+sLqK2yePL09NbHRMRETlWSrRFpNez770BK5ZgLv8CvnMv7dQ59c0eb+yo4OJxA8lKigpzhCIiciJSQaKI9Gq2KB/7+EIYNR5z9ic7fd6GwlqaPZg3XAsgRUQkPJRoi0ivZb0g3kO/BZ8P3xe/g/F1fsv0Nfm1BHwwMSMxjBGKiMiJTIm2iPRa9qUnYdtGzGe+gkntf0TnrimoZXRaDDERnU/ORUREjoQSbRHpkeyqD/D+8Uds7p7WxyrK8J54EPvc45gZ80ILII9AVUOQHaX1TBwYd/jBIiIiR0mLIUWkR7HNzdin/o595enQ12/9DzP1FMxFDiSlYF/+L3bxC9DcjJmzAON86Yg7hqwrqMUCE9Njw/AOREREQpRoi8gxsc3NULAPm7sL6moxSf1CLfWSUyAp5YiSYFtWgrfwnlA5yPwLMBdegV30EvaN57DL34WIyFCCPft0zEVXYgZkHFXMawpqiA4YRqbGHNX5IiIinaFEW0SOmG1owL7wBHbtcsjPgebmj44dPHD8NHw33IyJOnz7PLt5Ld5f7oHGBsyXv49v5mkAmEs+iz3nU9jXn4PKMsyZF2MGZR5T/GvyaxnbP5YIv3pni4hI+CjRFpEjYrdvwnv4PijIhbGTMeOmQGY2ZvBJEJcAlWVQXordswP7/BN49/0c3zd+holpv0zDW7II+8j9MGAQvht/1CqRNnHxmIs/3SXxl9Q2sbeykbOGJ3XJ9URERNqjRFtEOsU2NWKf+WeodrpfKr7v3o4ZM6n1wJQ0AMzkWXiDMrF//Q3eb27B9+1bMXEJh17TWuzzT2Cf/SecPBHfjTdjYsO7FfragloALYQUEZGwU6ItIh2ynodd/h722ccgPxcz7xzMFV/scIZ6P9+MedjIKLw/3433qx/j+8YtkJyK8fuxzU3YR/+Ife/10KLGa76GCUSE/f2szq8lPtLH0H7aDVJERMJLibaItMlaCyvfx3v2n5C7GwZl4fvWrZjxU4/oOmbSTHzf+BneH+7Eu/m60JORkeCPgLoazMWfCS1sPMLOIUfDWsva/BompMfiOw6vJyIiJzYl2iLSii0vxft/d8DubZA+GHPd9zAz5h7RzosHM2Mn4/vxr7EbVkF9XcuvWszYKZhpp3Rx9O3Lr26iqLaZS8epbERERMJPibaItGL//TDk7sZc+23MrNMx/mPfPdEMzsYMzu6C6I7emvyW+mz1zxYRkeNAO0OKyCHstg3YD9/EnHsJvlMWdEmS3VOszq8hJSbA4MTI7g5FREROAEq0RcLM1lTjffgWtrS4u0M5LOsF8R5/APqlYc6/vLvD6VJr8mtYsa+Giemxx6UeXERERKUjIh9T0xgkt7KRUWlHv2ugra3BrvoAu+wd2LAKgs3YEWPx3XRXj07y7Luvw57toZrsqOjuDqdLNHuWx9cU8+T6EjISI3EmpHV3SCIicoJQoi1ykKBnufPNvWworONX52Uf1RbdNn8v3v/9AOpqIKU/5sxPQEQE9gUX++FbmFmnhyHyY2drq7FPPQojxmJadmXsbfZWNlDfZIkMGKL8hromjz9+mM/m4nrOGp7El6enEx3QD/JEROT4UKItcpBnN5WyvrCOSL/hL0sLuOfc7CNqA2c9D+/RP4AB3w/vhuFjANhRWkf6+jXE/Odh7KSZmOijny0PF/vcE1BdGWrh14Nn3dtireXf60t4bHXr8pzYCB/fPzWDeScldkNkIiJyIlOiLdJiV1k9/1hdzOyseOZkJfDb9/J4bXsF54xI7vQ17Duvwpb18LmvszNlGG+vKuKd3ZUU1jRzzswvcoN7E/ZFF3Pp59u/xp4deA/eG9oY5qyLj09/6Z1bsYuex8w9G5M9POyv15U8a3loRSHPbSrjtJMSmZudQGOzpTHo0ezBlEFxDIgP/0Y4IiIiH6dEWwRoCnr89r084iN93DitP4mNVbwyIIa/rypiTlYCCVGH77xhy0ux//kbpWNmcmf1SHa+tAu/gcmD4hgQH8lbJXV8Yc5ZRL/6DPbUsyGtda2wLcrHu+9Wcm00+15/j8rdNVTPWECV52NM/xhmZia08cptxFJThX3vDagog+oKbFUlJiYWc+WXMQmHzuzayjK8P/5faMfGS6/p3Ad2HLy2vZwXt5TxrTkZZCe3vYtjs2e5f0kei3dV8onR/fjitAHaiEZERHoMJdoiwD/XFLOrvIFb5meS+J+F2Hdf48tzLuK7UfP4x+oibpw5EABbX4t95zXsyiWYSTMxZ1yIiQi1irP/eoCm5iC/GnUleVWN3DAjnVOHJJAYHWBzcR03/W83b0+/jLNXvov3xIPwi98fEoOtLMf73c9ZHzuYn538eez+A+vKAegX7Wf64PhOJZLeQ7+DNUshEID4JEhIxG7Mxe7ciu9bP8cMGBR6zeZmvL/cA7VV+H54Dyb+2Msr6ps9thTXsbm4jgnpcZzc/8jLZIpqmnhgWQH1zZabX9nNTfMGM2XQoZvM5Fc1snBZAcv31XD1pDSuGJfa60peRESkb1OiLSe89YW1PLWhlHNHJDOtYiveO6/CiDEM+fBlzh/q40V7Cmcl1jN8w5vYN1+G2hroPxD774exrz8X2kI8Nh67/F0eOueHbK4IctO8DE4d8lHSOio1mpOSo3glt4lzLroK+5+HqX3pSexJoyG1PzQ24P3+F3jlpTxy9ndItQFuPm0wCbnb+QEZ6gAAIABJREFUiH/0Pt6PG8r9Iy9jR2kDI1I77gZiN6+FNUsxl16DOe+yA8mn3bYR7//dgXf3Tfi+8TPM0JHY/zwMW9aHuowMGdbpz2xXWT3Pby4jv7oJvwG/z+AzhrK6ZnaU1eO1/C8hKaqM3184lOSYzv9VY63lL0sLsBbuOnsIf1lawC8W5fCVGemcOyKZNQW1PL+5jKV7q/EZuGFGOueP6tfp64uIiBwvSrTlhLa+oJbfvLeP9PgIvjA+Ee/2n0L6YHzfvR2qKvj0sy7vNlbzp0V7+fK2ZZw0ZgrR53wSM2w0dtMavP/+Hfu332OB18ecx/8aU7l0bMohSTaAMYZzRiSzcFkBO84+m6FL3qBq4b2hg/4AxMRCbTVLrv4523LgW3P6hzqepE7A/uSXTPnL7zDWY9mmXEac2n4NtfU8vH8/DClpmDM/ccgMrxkxBt/Nv8S77za8X/8YM/ds7BvPY876JL5OdEKx1rI6v5anNpayKq+GKL9heEo0jRY86xH0LLGRfi4bm8rYATHERfr56Wt7uP/9PH46P7PTs81LcqpYmlvNtVP7M3ZALHedM4Rfv7OPP31YwJPrSyisaSYpys8V41M5b2QyqbGqvxYRkZ7JWGsPP6p3sPv27evuGHqFtLQ0iot7/uYp4VRQ3cjfVhbx3p4qUmMD/Oi0wQx/7Z/Y157B94O7MKPGHRj71ort/GZjIxaD38CQ5ChGpEQzIjWa4SnRZO9cyY4lS/lJ6rmMT4/lZ2dk4fe1TiqrG4Nc+99tLBiWxA2TkkmqKKZ88wYozIPiApqnzeNrewcQF+nj3vNOOuQatrKMH/xrBcbv555rTsVEtJ1ceh++hX3g15hrv43vlAVtjrGVZXi/vx12b4PRE/B95xeH3f2xKejxs9dz2FBUR79oPxeO7sd5I/sdtnb9+c2lPLCssNOzzjWNQb72/E76Rfv59UGfQdCzPLKykE3FdZw7Ipl5JyUS6e+aNn36fugZdB96Bt2HnkH3oWdo7z5kZGQAdGr2SDPacsJ5YXMZD68oxGfg0xPTuGRMCpF7tuK9/ixm/vmHJNkAp00dztiTm9haUs+2knq2ldbzfk4Vr26vACDgSyUw4HxSovx8b+7gNpNsgPhIP3OzE3hzZyVfmDKA/mMn4xuQeeD4SxtLKawp5LZZrRN1k9iP6UNT+VdBJOVPP0G/Kz7b6vq2qSnUBztzKGZ2+zPUJrEfvu/fiX3nVczs+Z3aYv2pjaVsKKrjumkDOG9kMhGdTHIvGNWPpbk1PLSikAkDY8lMbHtR436Priqior6Zn5x+6Ofo9xm+OC29U68pIiLSUyjRlj6lrsnj52/kMDsrnkvHprY6viqvhgeWFTA1I46vzhpIWmwEtrkJ75H7W7putN12Ly02grTYCOZkhbp+WGsprGk6kHjvrWzkMxPTSDzMDO85I5J5Y0cl7+yu5NODBhx4vrohiLuumMmD4pj8sUV/+02bOprHX97NytXbOGPiWszoCYcct2++CMUF+L5zG8bXcRwmOgZz1sUdjtkvr6qRf68r4ZQhCXzi5JROnbOfzxi+OXsg33phJ799N49fnptNoJ3/iKwtqOHlreVcNLrfUW0UJCIi0tNoizTpU57ZVMrm4joeWVnEMxtLDzlWXNvEve/uIyshwA8GVpJasAu7dxf2mX/Cvj34rr4RExPbqdcxxpAeH8mp2Yl8fsoAfnJ6JkP7HX7L8pPTYshKiuSVbeUHngt6lsfWFFHT6PGFKf3bPXd4SjTJUT6WZ0zBe+i32NrqA8dsTRX2eRfGTsGMndKp99AZ1loWLi3AbwzXTRtw+BPakBobwVdnDWRbaT0PLiugKei1eo3nNpVy6xs5pMdH8JlJ2iJdRET6Bs1oS59RXt/MUxtKmZUZaoH30IpCIv2G80f1o9mz3PP2PhqbmvnBsj8R+dwuDk73zMzTMJNmhD1GYwznjkjmweWFLNlVyvIdxbyyrZySumbOHp7UYbLuM4apgxP4MDia4OpyuPWbYAzUVENDHRiD77LQjHxVQ5CVeTVEBwxxEX7iIn2kxUYQ34l+4Ad7b08VK/JquG7agGNadHjKkEQuHF3HC5vLWJVfw3XT0pk+OJ7qhiC/fz+PD/ZWM2NwPN+aM4jYiCOLUUREpKdSoi19xr/XldAY9Lhmcn/S4yO5+629/HlpAVEBHztLQ32dv7vhcQZHBvF9/aehJLWpCbAwYfpxi3P+0CQeWVnE95/ZgCG0c+FXZoQSz8OZPjiON3ZUsOWq7zFm/SJMbDzEJUBcPGbYKMyQYVTWN/Pj1/aQU9F4yLkxAR8Pfmp4p5Pt2qYgDywvZHhKFBd0Qfu866enM2NwPA8sK+D2xXuZlhFHTkUDJbXNfHHqAC4+uZ/6YIuISJ+iRFv6hILqRl7eWsaZw5LITAotuPvhaYO5Y/Fe7l+ShwdcsPcd5mUnYK75ESa6+2qAE6L8XDd9ADU2glMHRTIwIbLT504eGIfPwMp+oxj/9VNbHa9tCnLror3kVzVx82mDSYsNUNPokVsZ2tzl3T1VnDuyc1vK/2N1MeV1rRcmHospg+K474KhPL+5lH+tLSExysdd52QzOk012SIi0vco0ZY+4Z+ri/EZw6cnpoXqrtevILB7Oz/cs5tfpp9D0OfnC9MGYs78Uo+YNT1vZL+jat8UF+lnbP8YluVW87nJh9ZzNzR73LF4L7vK6vnRaZnMyPxohnzSwFhe2lrGGzsqOpVo7ylv4KUtZVwwKrnLFyZG+A2XjE3l7OHJRPgNUQEtFRERkb5Jibb0ervK6nlzVyWXjE0hpbES787vQnMzpPQnOns4tw6pg4kz8B3Bzoc92bTB8Tyysoji2ibSWuqmm4KWu9/KZUNhHd87NeOQJBtCteFnDE3i76uK2FfZSEZix7Por20vx2fgqontL848VkdaLy4iItLbKNGWXu/vq4qIjfRx2dhU7OJnoLkZ38/uw2QN7e7QwmJ6RijRXrq3msykSN7dXcX7OVWU1Qf52qyBzDspsc3z5g9N5B+ri1i0s4KrJ7WfQAc9y5u7KpkxOP6w7QpFRESkfUq0pVdbX1DL8n01fH5yf+IifXjvvQHDRvfZJBsgKymSAXEB/ry0AIBIv2H64HjOHJbU4YLK1NgIJg6MY/HOCj49MQ1fOyU0q/JqKK8PMn9oUljiFxEROVEo0ZZeq6HZ4y/LCkiJCXDh6H6wZzvs24O5+sbuDi2sjDFcOSGN1fm1zM6MZ9rgeKI7Wed8xtBEfvteHusLa5mQ3vbGOIt3VpIQ6WNaxuG7oIiIiEj7tApJeq0Hlxewu7yBr88aSFTAh12yCAIRmBnzuju0sDtreDLfOzWDU7MTO51kA8zJSiAm4GPRjso2j9c2BXl/bxXzTkokwt/9i0ZFRER6MyXa0ist3lnBK9squGxsCtMGx2Obm7AfvImZNBMTp5nY9kQFfJyancC7e6qob/ZaHX9vTxWNQauyERERkS6gRFt6nb0VDfzpw3zG9o/5aFHfuuVQXYk5ZUH3BtcLnDE0ifpmj/dzqlodW7SjgoyESEalHn47eREREemYEm3pdf6ytIBIv4/vz804sJGK994bkJAE46Z2c3Q939gBMQyIi2DRjopDni+sbmJdYR1nDEvsEb3GRUREejsl2tKrWGvZUlLPvJMSSW3pIW2rK2HNMsys+Ri/2tEdjs8YzhiWyOr8WpbnVtPsWQAW7wol3qe30x5QREREjoy6jkivUlzbTH2zR9ZBG67YD9+CYLPKRo7AmcOSeHFzGb9YvJe4CB9TMuLYUlzH+AExpMd3fkt4ERERaZ8SbelVcioaABiSFHXgObtkEWQO7dO9s7taenwkD14ygtV5NXyYW82y3GrK64N8Jow7QYqIiJxolGhLr5JT0QiENm0BsHk5sGsrxvlSd4bVK0UHfMzKSmBWVgKetRRUNzEwPqK7wxIREekzlGhLr5JT0UBSlJ/E6NAfXfvu6+DzYWad1s2R9W4+YxiUoJIRERGRrhT2RNtxnL8CY4EXXNe940jGOI6TDrzsuu6UcMcpvcOeikaykkNlI7ayHPvmSzB5NiaxXzdHJiIiInKosHYdcRznUsDvuu4cYJjjOCOPcMyvgZhwxii9h7WWvRUNBxZC2mf/CU2N+C75XDdHJiIiItJauNv7zQfclsevAHM7O8ZxnAVADZAf1gil1yita6amySMrKQq7bw/2rVcwp5+PGTi4u0MTERERaSXcpSNxQG7L41Kgrd1EWo1xHCcSuAW4BHi6vYs7jnM9cD2A67qkpaV1Udh9WyAQ6JWf1c495QCMH9KfwCN/pikmlrTPfxVfYnI3R3Z0eut96Gt0H3oG3YeeQfehZ9B96Bm64j6EO9Gu5qPSj3jankFva8zNwB9d1y13HKfdi7uuuxBY2PKlLS4u7oqY+7y0tDR642e1bk8pAIlbltK4fAnm8mspbWyGXvheoPfeh75G96Fn0H3oGXQfegbdh56hvfuQkZHR6WuEu3RkOR+Vi0wCdnVyzFnA1xzHWQxMdhznwbBGKb1CTkUjCZE+Ev73BKQOwCy4qLtDEhEREWlXuGe0nwbedhwnAzgfuMpxnDtc1/1pB2Nmu677z/0HHcdZ7LrudWGOU3qBnIoGMhMjMTu3YhZchIlQz2cRERHpucI6o+26biWhxY7vA2e4rrv6Y0l2W2MqPnZ8fjhjlN7BWktORQNZgUZoboLs4d0dkoiIiEiHwt5H23XdMj7qKnLUY+TEVtEQpKrRI7OhDACTPaKbIxIRERHpWLhrtEW6RE5FAwBZZXsgOgb6D+zmiEREREQ6pkRbeoWcikYAMveuhyHDMT790RUREZGeTdmK9Ao5FQ3ERvhI2b0Bo/psERER6QWUaEuvkFPRSFa0xTQ1whAl2iIiItLzKdGWXmFPRQOZthrQQkgRERHpHcLedUTkWFXWN1NRHyTL5ENUDKR3fkcmERERke6iGW3p8XIqWxZCFm6DrKFaCCkiIiK9gjIW6fEOtPbbvVYLIUVERKTXUKItPV5ORSPRfkirLgTVZ4uIiEgvoURberycigYyA40YwKjjiIiIiPQSSrSlx8upaCSrsQwio2DQ4O4OR0RERKRT1HVEerTqxiCldc1klue0LIT0d3dIIiIiIp2iGW3p0fYvhMzM36yyEREREelVlGhLj7ajNJRoDy3bpYWQIiIi0qso0ZYebUdZPYm+IKkNFWrtJyIiIr2KEm3p0baX1jPcVmIiImFQVneHIyIiItJpSrSlx2oKeuwpb2Bo5V7IPAnj10JIERER6T2UaEuPtau8gaCFYXkbVDYiIiIivY4Sbemx9i+EHFa6E9RxRERERHoZJdrSY20vrSfWeKTXl2KGn9zd4YiIiIgcESXa0mPtKKtnWFMxJiVNCyFFRESk11GiLV1q8c4KvvvSToKePabrNHuWXWUNDCvcihk/DWNMF0UoIiIicnwo0ZYu9cHearaXNrC5uO6YrrO3ooEmzzKsfDdm3NQuik5ERETk+FGiLV1qe2k9AMv31XTJdYbV5sPJE485LhEREZHjTYm2dJnqhiAF1U0ALN9XfUzX2l7WQLTXxKCMNExsXFeEJyIiInJcKdGWLrO9LDQLPXlgLDvLGiiubTrqa+0orOakqr0Exk3pqvBEREREjisl2tJltpeEEu0rUmoBWHGU5SNBz7KzvIFhVbmY8arPFhERkd5JibZ0me1l9QygnpP/fDP9Y3wsyz268pG8qkbqrY9hzWWQObSLoxQRERE5PpRoS5fZXlrPsOpcjOcx1ZawOr+GpqB3xNfZVhKaER+RkYzx6Y+oiIiI9E7KYqRL1DQGyatqYljhFgCm7Xqf+mbL+sIjb/O3Y3cBkcEmMseM6uowRURERI4bJdrSJXa0LIQcVp2LmT6X8VveIcJ3dN1HthdUkV2Tp4WQIiIi0qsp0ZYusaO0AYBhDSWYK64l2gYZT8UR99OubgiyvSmKYaYGk5AYjlBFREREjgsl2tIltpXWk9pURfLQbExKfxgzial7l5Fb2UheVWOnrtHsWX752jaa8LFgoD/MEYuIiIiElxJt6RI7imsYXrEbM2oCAGbW6UzNWQZ0vnzkgWUFrCm33LD7BUafvSBssYqIiIgcD0q05ZjVNgXJrW5mWNU+zMktifbU2QwKVpFBLctzD18+8sLmMl7eWs6n9izmzFPHY+Liwx22iIiISFgp0ZZjtqusAYthWEMRDBkOgImOxUyaxdT8NawtqGVfZfvlIyvzanhweQHTq7Zzdd06zGnnHa/QRURERMJGibYcs+2lLR1HBiRg/B/VVpvZ8zkjZwl+PL7xwk4eXVVEffNHfbWttWwtqeNXb+eS5avnO6v+RoTzxUOuISIiItJbBbo7AOldrLV4Fvw+c+C57fmVJDdUkjpq5KGDx05hqKnhD1Wv8Oj4K/jP+hIW7ajgvJHJ7K5oYH1hHWV1zSRF+vjRsj8TM2a8tlwXERGRPkMz2tJptU1BfvzqHr794k7K65oPPL+tqJrh1bmY0eMPGW8CAcyMufRb9TbfHmG4+5whJMf4eWxNMRsL65iQHsuNM9P5TeM7DKjKx+d88Xi/JREREZGw0Yy2dEp9s8fti/ayqbiOgM/wszdyuPOsIUT4DbkNfmbXFcKQYa3OM2dchP3wbbw7v8fJX7mJX583icr6IEnRfowx2Nw9eG8+i5l/PmZQVje8MxEREZHw0Iy2HFZj0OP/3gwl2d89JYOfnJ7JvspGbn0jhw2FtXjGMDw5gPG1rq02gzLx/eRe6JeK97tb4fVnSYr2Q3EB3n8fwbv3JxATg7n408f/jYmIiIiEkWa0pUNNQcsv38pldX4t35oziLk2H7s7l5tmT+LuJYX88q1cAIYPSW/3Gqb/QHw334P30G+xT/wV+85rsG8PYGDidHwXXIGJ1y6QIiIi0rco0ZYO/XV5Acv21XDjzHTOyIjA+8kdUFnOtOgYvjvzcu6140lsrCFt7MkdXsdEx+C74Wbsi//GLn8Pc9FVmLlnY1LSjtM7ERERETm+lGhLu5o9y5u7KjljaCLnjeyH99Q/oLIc87mvwbYNzHn/CX6YsIza2CRM1s2HvZ7x+TAXXQkXXXkcohcRERHpXkq0pV0bi2qpbfKYlZWALSnCvvo0Ztbp+E47F047F3vVl5n54duYxCSMT+X+IiIiIgdTot3HWWsBMMYcZmRry3JrCPgMkwbGYv+2MHSdS645cNzExmPmn981gYqIiIj0MUq0+7DtpfXctiiHivogAR/4jKFfTIC7L44mpRN599LcasanxxKTsw3vwzcxFzqY1P7hD1xERESkD9DP+/uowuombl+UQ4TPcOWEVD41JpULR/Wj2bN8/5kNFNU0dXh+XlUjuZWNTM+Iw3P/Ckn9MOdddpyiFxEREen9NKPdB1U3BPnF4hwag5a7zxzCkOSoA8fOGJbEj1/dw22Lcrj77Gzio1r3vgZYllsNwNSSjbB9E+bz38BExxyX+EVERET6grAn2o7j/BUYC7zguu4dnRnjOE4S8C/AD9QAV7qu2xjuWPuCpqDHXW/nklfVyK0Lsg5JsgGyk6O46xNj+M5T67nrrb3cuiCLCH/rH2wsza0mMzGSgW/8BwZnY05ZcLzegoiIiEifENbSEcdxLgX8ruvOAYY5jjOyk2OuBn7juu45QD5wXjjj7Custdz/fj7rCmr55uxBTEiPa3Pc1MxkvjVnEOsK67hvSR5ey4LJ/WqbgqwvrGV6ioE92zFzzmhz10cRERERaV+4Z7TnA27L41eAucDWw41xXfePBx3vDxS2dXHHca4HrgdwXZe0tBN785PtxTW8uauSL8zM4rIZ2e2OCwQCXDp9GHUmkj++s4vstBpunHvSgeOLtxXT7MHchr0ApCy4gMAJ/tmGQyAQOOH/zPYEug89g+5Dz6D70DPoPvQMXXEfwp1oxwG5LY9LgalHMsZxnDlAP9d132/r4q7rLgQWtnxpi4uLuyLmXmvp9nIAZqZH0NFnkZaWRnFxMecMiWLHyGT+sXwvGTEep2aHtkF/Y2MecZE+hix/CQZnUx4RDSf4ZxsO+++DdC/dh55B96Fn0H3oGXQfeob27kNGRkanrxHuriPVwP4VdPHtvF6bYxzHSQHuB74Y5hj7jG0l9cQEfAxKiOjUeGMM101L5+S0GH7/fh57yhvwrGX5vmqmpEUS2LoBM2VOmKMWERER6ZvCnWgvJ1QuAjAJ2NWZMY7jRAL/Bn7kuu7uMMfYZ2wrrWd4ajS+I9icJsJvuGleBtEBH3e9tZc1+bWU1weZ1rAXrIeZMjuMEYuIiIj0XeFOtJ8GPuc4zm8AB1jvOM7HO498fMwLwJcIlZD8xHGcxY7jXBnmOHu9Zs+yq6yBESnRR3xuamwEN80bTEF1E3e9lYvPwJSt70DqAMgaGoZoRURERPq+sNZou65b6TjOfOBs4B7XdfOB1YcZUwH8qeWXdFJORQNNnmX4QYm2tRa77F1oqAv1wI6OgbgEvLjYVuePGxDLF6cN4IFlhZycEkni2x9i5l94VFu3i4iIiMhx6KPtum4ZH3UVOeox0rFtJfUAh85or1+BXXgPAAc38CsyBgZmYoYMgyHDMVNmY/oP5MJR/Whotgwr2grNzZipqs8WEREROVraGbKP2F5aT2yEj4EtCyGttXjPPg4p/fF9/05obID6OqgqJ6akgJqNa7Fb1sMHb2Jf+je+79+FGTyEy8al4i18CJuQBMNHd/O7EhEREem9lGj3EdtK6xmWctBCyPUrYecWzGe/iuk/8JCx8Wlp1Le0q7F5OXj33oL321vw3XQX9EvDrlmGmTlPm9SIiIiIHINwL4aU4+DjCyGttXjPPQ4paZhTz+zwXDMoC993fwHBZrx7b8G++3qopltt/URERESOiRLtPmBP+ccWQm5YBTs2Y86/AhM4fE/t/9/evQdXWd4JHP++JwHCHQSlBAgXFRQjgmDx1qpM79X+0WmfarvdaW3X2tm203bdsY5dnXFrL9tdu7PdrrvadsfOunWera63XrSti9ZrF1wsWm+gXARRQgghF5KQ8+4f54AQEjgknEtPvp+ZM5zznudNfsmPk/PLk9/zPkl9A5kv3wCdHaS335xbNHnKoiJHLUmSVN0stKvAuua3FkIePJv9roI/RjL7RDJfug5G1ZEsOYdkRGGb3kiSJKl/9mhXgfXNexi7byHk82tg/Qskn7jyqIvl5KRTyXzrVhh59NfiliRJ0sEstCtImuYuwne0165en18ImQDZ++6AyVNJznv3oGJIxk8c1HmSJEk6mIV2Bbnp8dd5bGMrdSMyjK7NUFebYfakUVx1fv2A26r39Ka8urOLixdMhk2vwLrnSS69wtYPSZKkMrNHu0KkacrTW9uYO7mOi+ZO5Iy3jWXCqBoe27SbTS1dA563eVcXe7Nprj/76ScgyZC8/Z0ljFySJEn9cUa7QjR37qWtO8uKeRP54ILJAGxv7+Gzd69n7RsdzJncf9/0/oWQU+pI/+8JmH8ayfgJJYtbkiRJ/XNGu0Js2JmbtZ4zadT+Y1NHZ5g2poa1b3QMeN66HbmFkNPa3oTXN5MsObvosUqSJOnInNGuEBvz7SGz84V22tFO9gc3cnrtaTzes4zebEpN5tA+7X0LIVnzFADJYgttSZKkSuCMdoXY0NLFlDG1jBtVQ9qyg+x3r4GXn6Ox6UU6enILHvvq6U3Z0JLbETJd8yTMPolkyvFliF6SJEl9WWhXiI0tXcyZNIp022tkv301bN9G5kvX0dizHYC1b7Qfcs6m/ELIE+t6cjtBLl5e6rAlSZI0AAvtCrA3m/Jaaxezk3ay37kaurvIXHUjSeNSpiw8hRmdTfxh26GF9vr8Qsh5W58DIFlyTknjliRJ0sAstCvAltZu9mZh1upfw8g6Mld/h2TOyQAki5fT2PwSf3yjnb3Z9KDz1rzezvhRNUxb+yicUA/1s8oQvSRJkvpjoV0B9i2EnLN5LcmF7yeZVv/Wk6cu5vTdG9mTTfbPYAPs6Ojhic27WTFrNMmLa0mWnH3UO0pKkiSpeCy0K8CGnXuoIaW+YzvJKYsOei4ZVcdpbxsLcFD7yK9ebiFN4X3dr0Bvr5f1kyRJqjAW2hVgY0sXM9M2RowaCQ0nHvL8pEWLmd32Oms37gCgpzfLA+taWDZjHNOefQwmHgdz55c6bEmSJB2GhXYF2NjSRUPrFpjfSFJTc8jzyRln0diynudbeunpzfLoxt3s2tPLB08cB88+TbJkOUnGVEqSJFUSq7Mya+vuZXvHXmbveIVkwen9jkkmTKZx1B66yfDSjj38/KWdzJwwkjOaXoDuLttGJEmSKpCFdplt2rcjZNu2Q/qzD9R4cj1JmuXONdt4eccePjBzJOmdt8G4CTC//wJdkiRJ5WOhXWb7t15Pd8PMOQOOG79kGXPbtrJ6ezejaxIuuPNbsKuZzF9eS1JbW6JoJUmSVCgL7TLb0NLF2N49TJnbcPg+6+mzaOzeBsCKN1YxurWZzFduIDnp1BJFKkmSpKNhoV1mG7fvZvburWQG6M/eJ0kSzj1hBJO6WvnAlsfJfPUGknkLShSlJEmSjpaFdhmlacrGXT3Mbn/9sP3Z+5xywXn8uPkeZnzhq+zbOVKSJEmVyebeMtrevpeONENDbytMP/L26cn0mdRcdWMJIpMkSdJQOaNdRhtacluqzzl+vNunS5IkVRkL7TLa8Np2ABpOOvJstiRJkv602DpSJs2de3l0426mdbYxdqHXwZYkSao2zmiXwcs7OvmrX25gW08Nl29bCcdPL3dIkiRJOsYstEts5au7uObBTdTu7eKbq77P25c32p8tSZJUhWwdGYKWzr30pilTxowoaHx8tonbn2mi8fg6rnr4n5kwcQTJRR8scpSSJEkqB2e0B6k3m3Ldbzdz48Nb6NqbPeL4bJry339sZll189E/AAAL6klEQVT9WK7veIwJb24k8/Er3T5dkiSpSlloD1JNJuGTi4/nleY9fO/xrWTT9LDjN+/qpqMny7mTe6l54E6St19AsqCxRNFKkiSp1Cy0h+CsmeP49Jkn8MTmNm5/pumwY19s6gRg/qN3Qc0Iko9+qgQRSpIkqVzsWxiiD50ymS2t3fzsuR3MmDCSFfMm9jvuxaZOxtdkmf7MSpKPXk4yaUqJI5UkSVIpOaM9REmScMVZ01g0bQw/eOr1/TPXfb2wvZP5rZtIps8iWXFxiaOUJElSqVloHwO1mYSr3zGDutoMv3xp5yHPt3X18lprN/PffJFk2XkugJQkSRoGLLQHKU1Tsg/cRfah+wEYN6qGM6eP4+mt7YcsjHxpR26We8GujSQNJ5Y8VkmSJJWehfYgJUlC+tJzpPf8J2lHOwBLZ4xlV1cv63bsOWjsi02dZEg5efdmsNCWJEkaFiy0hyDzocugo430ofsAOHP6WBJg1da2g8a90LSHhrSN0WPqYLKLICVJkoYDC+0hSGafBIuXkz54D2lHGxPqapk/dTSrtrTvH5NNU15u6uTk1k0w+0S3W5ckSRomLLSHKHPJZdDZTvqbewFYNmMs65v30Ny5F4DXWrtp78myYNsf7c+WJEkaRiy0hyhpmAdnnkP6m3tJ29tYVj8OgKfz7SMvbs8vhGzZYKEtSZI0jFhoHwOZSy6Fzg7SX9/N3MmjmDK6dn/7yAtNnYxLeqnv3A4N88ocqSRJkkrFQvsYSGbOJVl6Hulv7oP23SydMZY1r7fT05vyUlMn87M7ScaMhanTyh2qJEmSSsRC+xhJLrkMuveQrvwFS+vH0bk3y6qtbWze1c38llehwYWQkiRJw0nRtygMIfwIWAj8PMb4jULHFHJeJUlmNMD8RtInH2bRez5KbSbhjj80kQILXvsDydKF5Q5RkiRJJVTUGe0QwoeBmhjjOcC8EMLJhYwp5LxKlCy/AN7Ywuitr9B4wmg2tHSRACe3bIDZLoSUJEkaTordOnIhEPP3HwTOL3BMIedVnGTpuVBbS/rkSpbNyF19ZNaIbsb0dnnFEUmSpGGm2K0jY4Et+fvNwJkFjinkPEIIVwBXAMQYmTp16rGJetCm0nLW+fSsfox3XfZFfrj6TRZmW0jqxjB14ekkmcpoia+tra2A75XMQ2UwD5XBPFQG81AZzENlOBZ5KHah3QaMzt8fR/8z6P2NKeQ8Yoy3ALfkH6ZNTU3HIOShSRefQ/aJldStfZzPLJ3DovvvIp01hx3NzeUObb+pU6dSCd+r4c48VAbzUBnMQ2UwD5XBPFSGgfJQX19f8Mco9hTrat5q+zgD2FDgmELOq0ynL4MxY0mfephL5k9k1qtP2zYiSZI0DBV7Rvtu4HchhHrg/cClIYRvxBi/fpgxZwNpP8f+JCQjRuSuqf37R0hWXAzd3WChLUmSNOwUdUY7xthKbmHjk8BFMcZn+hTZ/Y3Z1d+xYsZ5rCVnXwhde8je99PcY684IkmSNOwU/TraMcadvHUFkYLHFHJexTppIRw3FdaugpEj4W0zyx2RJEmSSqwyLoNRZZJMJndNbYCZc0lqasobkCRJkkrOQrtIkuUX5f5tmFfmSCRJklQORW8dGa6SGQ0kH7+S5NRF5Q5FkiRJZWChXUSZiz5Q7hAkSZJUJraOSJIkSUVgoS1JkiQVgYW2JEmSVAQW2pIkSVIRWGhLkiRJRWChLUmSJBWBhbYkSZJUBBbakiRJUhFYaEuSJElFYKEtSZIkFYGFtiRJklQEFtqSJElSEVhoS5IkSUVgoS1JkiQVgYW2JEmSVAQW2pIkSVIRWGhLkiRJRWChLUmSJBVBkqZpuWM4VqrmC5EkSVJFSwoZVE0z2om3wm4hhNXljsGbeaiUm3mojJt5qIybeaiMm3mojNsR8lCQaiq0JUmSpIphoS1JkiQVgYX28HRLuQMQYB4qhXmoDOahMpiHymAeKsOQ81BNiyElSZKkiuGMtiRJklQEFtqSJElSEdSWOwAdOyGEicAdQA3QDnwMuBlYCPw8xviN/LgfHXgshDAZuB04AVgdY/xcOeKvFkeRh2nAz2KM78g/HgHcBRwH/CjG+OMyhF81hpCHBuAnQBZYB3wuxmiP3RAMNhcHnN8IfC/G+O6SBl5ljkEe7gP+Jsa4pqSBV5kh/GyaB9wKTAHujDH+bRnCrxqF5KG/MTHG7r511OE+jzPa1eUTwE0xxvcA24BLgZoY4znAvBDCySGED/c9BnwSuD3GuAwYH0JYVq4voEoUkofJwG3A2APO+yK5X3TOAz4SQhhf6sCrzGDz8Dng8zHGFcAs4PQSx12NBpsLQggJcBMwosQxV6Oh5OETwHqL7GNisHn4AnBdjHEx8N4QwvGlDrzKHDEP/Yx53wB11ICc0a4iMcZ/OeDh8cCfAf+Yf/wgcD6wBIh9ju0AGkMIk8gVFptLEnCVKjAPd5L77fmeA8ZeCHwtf/8RYBnwP8WMtZoNNg8xxmsPOG8K0FTcSKvfEF4TAJ8m9zp4b5HDrHqDzUMI4TjgH4CbQwgXxRj9uTQEQ3g97AAWhRDWAaOAluJHW70KyUM/Y94EPs6hddTLA30eZ7SrUAjhHGAyuYJ5S/5wMzCN3G/HfY89CswGvgQ8nz+uITpcHmKMrTHGXX1O6S83GqJB5GHfeR8Dnosxbi1NpNXvaHMRQphC7s3v70saaJUbxGviK8B/Af8G/HkI4UMlC7aKDSIPvwLOJvde/RCwt1SxVrMj1EwHjYkxPslRvldbaFeZ/MzD94HLgTZgdP6pceTy3d+x64ErY4w3AC+Qm0HSEBSQh/4UOk4FGmQe9vVCXgV8udgxDheDzMW3gWtijD3Fj3B4GGQelgA/iDFuIzeTd2GRw6x6g8zD14BP5f/qNhpwzcIQFZKHPmMYaNxAfCOvIiGEkeRmHa6JMW4EVpP7kwbAGcCGAY5NBk4PIdQAywEXfg1BgXnoT6HjVIDB5iHfG/lT4PKBZrt1dIbwmrgA+E4IYSWwOIRw2EVHOrwh5GEdMC9/fxmwsYhhVr0h5GEuMCuEUAecie/VQ1JIHvoZQ3/jDvd57NGuLp8h9+K7NoRwLfDvwCdDCPXA+8n9ySkFftfn2Lr82NnAE+SKDA1eIXnoz23AL0II7yC3mvmpUgRbxQabh68BDcD3QwgA18cYHy5BvNVsULmIMc7fdz+EsDLG+PVSBFvFBvua+Dvgh/lzOoAPlyLYKjbYPFwPrCTXK3w/ufYRDV4heeg75mbgbg6towbkzpBVLj87927gkfyf/fo9puIq9Huef+GeDzzgbOqx5//9ymEuKoN5qAzmoTIcxXt1wfmy0JYkSZKKwB5tSZIkqQgstCVpmAkhvHLgJgshhG+GEObn79flF0ZLkobIxZCSVEXyu8X9+oBDT8QYP99nWE/+ts82IIYQzgX+F+gJIey7Ru9IYGSM8ZRixSxJ1cpCW5KqSw0wKcY4J4RwIfDX+c13JgO95K48NB64NITwe+Cd5LY4/32MsQM47cAPFkKYw6G7NUqSCmChLUnVpbefxwm5VsFs/ti+VfAJ8Fngn4DjQgir+pz7ZeA1vF6vJA2KPdqSVF2yQH0IYQ3wQyAbY7wDeDDGeEuM8VZgJ/AfMcbfktvGOUtuh7NHY4zLYozLgGd5a/czSdIgWGhLUnXJAltjjIvJzVYTQpgAPBRCOPUI510WQliVn9m+GGeyJWlILLQlqboc8nM9xtgKfAv4iyOc+9MDZrTvL0ZwkjSc2KMtSdWlhrdaR8YBz+eP/2uM8XAz1P1NvCTHOjhJGk6c0Zak6lLDwa0jtQBHKLIB9gArDmgdWcrBlwCUJB0lZ7Qlqbp0AQ/m7z8CPLbviRDCccBMYAq5RZAAI4BMjPFe4N6+HyyEcMYBYyVJR8FCW5KqSIyxGbgifz/LW5f0I3//VuC2GOO2/LHx5DalOUQI4SPAT4DvFi1gSapiSZq6qFySdKgQQh1QE2NsL3cskvSnyEJbkiRJKgIXQ0qSJElFYKEtSZIkFYGFtiRJklQEFtqSJElSEVhoS5IkSUVgoS1JkiQVwf8D4qviqeMHUI0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "neu_mean, _ = Neu_far['Neu_1M'].compute_mean_returns_spread (upper_quant=1,lower_quant=10,by_date=True,demeaned=True)\n",
    "mean, _ = basic_far['1M'].compute_mean_returns_spread (upper_quant=1,lower_quant=10,by_date=True,demeaned=True)\n",
    "\n",
    "neu_cum=neu_mean.cumsum()\n",
    "cum=mean.cumsum()\n",
    "\n",
    "print('提纯后的多空净值为%2.4f,原始因子多空收净值为%2.4f'%(neu_cum.iloc[-1][0],cum.iloc[-1][0]))\n",
    "plt.figure(figsize=(12,8))\n",
    "plt.title(\"多空收益率\")\n",
    "plt.xlabel(\"时间\")\n",
    "plt.ylabel(\"收益率\")\n",
    "\n",
    "plt.plot(neu_cum,label=\"Neu\")\n",
    "plt.plot(cum,label=\"M\")\n",
    "plt.legend()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Neu_far['Neu_1M'].plot_quantile_returns_bar(demeaned=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "剥离流动性后的提纯动量因子多空收益改善显著，且多头的稳定性 有比较明显的提升，是比较值得关注的动量因子改造和应用方式。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.风格中性后的残差动量因子"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "传统的价格动量效应，其实包含了对经典Fama-French 三因子的较高暴露。反之，基于残差的动量组合，由于排序标准是剔除了承担系统性风险所获补偿的超额收益，因此，据此构造的组合，将不会对风险因子有系统性的暴露，恰恰相反，该组合是纯粹基于股票的异质性表现来构造的。异质性收益与总收益类似，也表现出一定的动量（反转）特征。 下面我们就将基于这一理论，测试基于股票异质性收益的残差动量因子在中证500中的表现。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1残差动量因子：稳定性略有提升"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "使用 Fama & French 的三因子模型为每个股票来估算残差回报。采用相对简单的直接回归取残差的方法。假设当前时刻为 t 月月末的最后一个交易日，对于单只股票而言，我们将其 t-35 月到 t 月（共 36 个月）个股月度收益率对 Fama-French 三因子进行时间序列回归：\n",
    "\n",
    "$ r_{i,t}=\\alpha_i+m_iMKT_T+s_iSMB_t+h_iHML_t+\\epsilon_{i,t}$\n",
    "\n",
    "其中：SMB 为小盘股组合和大盘股组合的收益率之差，组合日收益率的 计算采用流通市值加权。HML 为高BP组合和低BP组合的收益率之差，组合日收益率的计算采用对数收益率。根据上述回归得到的残差变量即可认为是该股票在剔除了已知风格因子影响后的特质收益。\n",
    "\n",
    "由于A股市场动量因子表现的特殊性，即短期反转效应显著强于动量效应且选股能力突出。因此我们这里将从短期动量入手，尝试直接采用当期残差变量作为剔除风格影响后的特质收益动量因子，我们命名为Momentum_1M_Resid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "metadata": {},
   "outputs": [],
   "source": [
    "import statsmodels.api as sm\n",
    "from statsmodels import regression\n",
    "\n",
    "# 计算Fama French残差\n",
    "def Cal_FF_resid (stocks,tradDate,N,rf):\n",
    "    '''\n",
    "    stocks:list\n",
    "    tradDate:str,yyyy-mm-dd\n",
    "    N：int tradeDate前N天\n",
    "    rf:fload 无风险利率\n",
    "    -----------\n",
    "    return:df\n",
    "    |index-code|values|\n",
    "    '''\n",
    "    LoS=len(stocks)\n",
    "    #查询三因子/五因子的语句\n",
    "    q = query(\n",
    "        valuation.code,\n",
    "        valuation.circulating_cap, ## 用的流通市值\n",
    "        (balance.total_owner_equities/valuation.circulating_cap/100000000.0).label(\"BTM\"),  # 获取数据并重命名。计算BTM\n",
    "        indicator.roe,\n",
    "        balance.total_assets.label(\"Inv\")\n",
    "    ).filter(\n",
    "        valuation.code.in_(stocks)\n",
    "    )\n",
    "    \n",
    "    df = get_fundamentals(q,tradDate)\n",
    "    \n",
    "    #计算5因子再投资率的时候需要跟一年前的数据比较，所以单独取出计算\n",
    "    befday=get_trade_days(end_date=tradDate,count=253)[0]\n",
    "    ldf=get_fundamentals(q,befday)\n",
    "    # 若前一年的数据不存在，则暂且认为Inv=0\n",
    "    if len(ldf)==0:\n",
    "        ldf=df\n",
    "    df[\"Inv\"]=np.log(df[\"Inv\"]/ldf[\"Inv\"])\n",
    "    \n",
    "    # 选出特征股票组合\n",
    "    try:\n",
    "        S=df.sort('circulating_cap')['code'][:LoS/3]\n",
    "        B=df.sort('circulating_cap')['code'][LoS-LoS/3:]\n",
    "        L=df.sort('BTM')['code'][:LoS/3]\n",
    "        H=df.sort('BTM')['code'][LoS-LoS/3:]\n",
    "        W=df.sort('roe')['code'][:LoS/3]\n",
    "        R=df.sort('roe')['code'][LoS-LoS/3:]\n",
    "        C=df.sort('Inv')['code'][:LoS/3]\n",
    "        A=df.sort('Inv')['code'][LoS-LoS/3:]\n",
    "    except AttributeError:\n",
    "        S=df.sort_values('circulating_cap')['code'][:int(LoS/3)]\n",
    "        B=df.sort_values('circulating_cap')['code'][LoS-int(LoS/3):]\n",
    "        L=df.sort_values('BTM')['code'][:int(LoS/3)]\n",
    "        H=df.sort_values('BTM')['code'][LoS-int(LoS/3):]\n",
    "        W=df.sort_values('roe')['code'][:int(LoS/3)]\n",
    "        R=df.sort_values('roe')['code'][LoS-int(LoS/3):]\n",
    "        C=df.sort_values('Inv')['code'][:int(LoS/3)]\n",
    "        A=df.sort_values('Inv')['code'][LoS-int(LoS/3):]\n",
    "    \n",
    "    # 获得样本期间的股票价格并计算日收益率\n",
    "    df2 = get_price(stocks,end_date=tradDate,count=N,fields='close')['close']\n",
    "    # 0*df2[1:]主要是方便日期对齐并返回一个df\n",
    "    df3=np.diff(np.log(df2),axis=0)+0*df2[1:]\n",
    "    \n",
    "    #求因子的值\n",
    "    SMB=sum(df3[S].T)/len(S)-sum(df3[B].T)/len(B)\n",
    "    HMI=sum(df3[H].T)/len(H)-sum(df3[L].T)/len(L)\n",
    "    RMW=sum(df3[R].T)/len(R)-sum(df3[W].T)/len(W)\n",
    "    CMA=sum(df3[C].T)/len(C)-sum(df3[A].T)/len(A)\n",
    "    \n",
    "    #用中证500作为大盘基准 数据从2008-1-16开始\n",
    "    dp=get_price('000905.XSHG',end_date=tradDate,count=N,fields='close')['close']\n",
    "    RM=diff(np.log(dp))-rf/252\n",
    "    \n",
    "    #将因子们计算好并且放好\n",
    "    X=pd.DataFrame({\"RM\":RM,\"SMB\":SMB,\"HMI\":HMI,\"RMW\":RMW,\"CMA\":CMA})\n",
    "    #取前3个因子为策略因子\n",
    "    factor_flag=[\"RM\",\"SMB\",\"HMI\",\"RMW\",\"CMA\"][:3]\n",
    "    #print (factor_flag)\n",
    "    X=X[factor_flag]\n",
    "    \n",
    "    # 对样本数据进行线性回归并计算ai\n",
    "    t_resid=[0.0]*LoS\n",
    "    for i in range(LoS):\n",
    "        t_stock=stocks[i]\n",
    "        sample=pd.DataFrame\n",
    "        #np.linalg.lstsq(X,y)[0]==results.params\n",
    "        # 将中证500 2008-1-16前的空白数据填充为0\n",
    "        X=X.fillna(0)\n",
    "        #t_r=linreg(X,df3[t_stock]-rf/252,len(factor_flag))\n",
    "        t_r=np.linalg.lstsq(X,df3[t_stock]-rf/252)\n",
    "        t_resid[i]=t_r[1][0]\n",
    "    \n",
    "    #这个scores就是alpha \n",
    "    resids=pd.DataFrame({'code':stocks,'resid':t_resid})\n",
    "    return resids\n",
    "\n",
    "# 辅助线性回归的函数 Cal_FF调用\n",
    "def linreg(X,Y,columns=3):\n",
    "    '''\n",
    "    辅助线性回归的函数\n",
    "    X:list,array,DataFrame 回归自变量 \n",
    "    Y:list,array,DataFrame 回归因变量\n",
    "    -------\n",
    "    return：list \n",
    "    '''\n",
    "    X=sm.add_constant(array(X))\n",
    "    Y=array(Y)\n",
    "    if len(Y)>1:\n",
    "        results = regression.linear_model.OLS(Y, X).fit()\n",
    "        #return results.resid[-1] # 获取当期残差\n",
    "        #return results.params\n",
    "    else:\n",
    "        return [float(\"nan\")]#*(columns+1)\n",
    "\n",
    "# 获取因子    \n",
    "def get_Momentum_resid(dateList):\n",
    "    dict_=OrderedDict()\n",
    "    for d in dateList:\n",
    "        print(d,'success')\n",
    "        stocks=get_stocks('000905.XSHG',d)\n",
    "        data=Cal_FF_resid(stocks,d,20,0.03)\n",
    "        dict_[datetime.strptime(d,\"%Y-%m-%d\")]=data.set_index('code')\n",
    "    datas=pd.concat(dict_.values(),keys=dict_.keys())\n",
    "    datas.index.names=['date','codes']\n",
    "    return datas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2007-01-31 success\n",
      "2007-02-28 success\n",
      "2007-03-30 success\n",
      "2007-04-30 success\n",
      "2007-05-31 success\n",
      "2007-06-29 success\n",
      "2007-07-31 success\n",
      "2007-08-31 success\n",
      "2007-09-28 success\n",
      "2007-10-31 success\n",
      "2007-11-30 success\n",
      "2007-12-28 success\n",
      "2008-01-31 success\n",
      "2008-02-29 success\n",
      "2008-03-31 success\n",
      "2008-04-30 success\n",
      "2008-05-30 success\n",
      "2008-06-30 success\n",
      "2008-07-31 success\n",
      "2008-08-29 success\n",
      "2008-09-26 success\n",
      "2008-10-31 success\n",
      "2008-11-28 success\n",
      "2008-12-31 success\n",
      "2009-01-23 success\n",
      "2009-02-27 success\n",
      "2009-03-31 success\n",
      "2009-04-30 success\n",
      "2009-05-27 success\n",
      "2009-06-30 success\n",
      "2009-07-31 success\n",
      "2009-08-31 success\n",
      "2009-09-30 success\n",
      "2009-10-30 success\n",
      "2009-11-30 success\n",
      "2009-12-31 success\n",
      "2010-01-29 success\n",
      "2010-02-26 success\n",
      "2010-03-31 success\n",
      "2010-04-30 success\n",
      "2010-05-31 success\n",
      "2010-06-30 success\n",
      "2010-07-30 success\n",
      "2010-08-31 success\n",
      "2010-09-30 success\n",
      "2010-10-29 success\n",
      "2010-11-30 success\n",
      "2010-12-31 success\n",
      "2011-01-31 success\n",
      "2011-02-28 success\n",
      "2011-03-31 success\n",
      "2011-04-29 success\n",
      "2011-05-31 success\n",
      "2011-06-30 success\n",
      "2011-07-29 success\n",
      "2011-08-31 success\n",
      "2011-09-30 success\n",
      "2011-10-31 success\n",
      "2011-11-30 success\n",
      "2011-12-30 success\n",
      "2012-01-31 success\n",
      "2012-02-29 success\n",
      "2012-03-30 success\n",
      "2012-04-27 success\n",
      "2012-05-31 success\n",
      "2012-06-29 success\n",
      "2012-07-31 success\n",
      "2012-08-31 success\n",
      "2012-09-28 success\n",
      "2012-10-31 success\n",
      "2012-11-30 success\n",
      "2012-12-31 success\n",
      "2013-01-31 success\n",
      "2013-02-28 success\n",
      "2013-03-29 success\n",
      "2013-04-26 success\n",
      "2013-05-31 success\n",
      "2013-06-28 success\n",
      "2013-07-31 success\n",
      "2013-08-30 success\n",
      "2013-09-30 success\n",
      "2013-10-31 success\n",
      "2013-11-29 success\n",
      "2013-12-31 success\n",
      "2014-01-30 success\n",
      "2014-02-28 success\n",
      "2014-03-31 success\n",
      "2014-04-30 success\n",
      "2014-05-30 success\n",
      "2014-06-30 success\n",
      "2014-07-31 success\n",
      "2014-08-29 success\n",
      "2014-09-30 success\n",
      "2014-10-31 success\n",
      "2014-11-28 success\n",
      "2014-12-31 success\n",
      "2015-01-30 success\n",
      "2015-02-27 success\n",
      "2015-03-31 success\n",
      "2015-04-30 success\n",
      "2015-05-29 success\n",
      "2015-06-30 success\n",
      "2015-07-31 success\n",
      "2015-08-31 success\n",
      "2015-09-30 success\n",
      "2015-10-30 success\n",
      "2015-11-30 success\n",
      "2015-12-31 success\n",
      "2016-01-29 success\n",
      "2016-02-29 success\n",
      "2016-03-31 success\n",
      "2016-04-29 success\n",
      "2016-05-31 success\n",
      "2016-06-30 success\n",
      "2016-07-29 success\n",
      "2016-08-31 success\n",
      "2016-09-30 success\n",
      "2016-10-31 success\n",
      "2016-11-30 success\n",
      "2016-12-30 success\n",
      "2017-01-26 success\n",
      "2017-02-28 success\n",
      "2017-03-31 success\n",
      "2017-04-28 success\n",
      "2017-05-31 success\n",
      "2017-06-30 success\n",
      "2017-07-31 success\n",
      "2017-08-31 success\n",
      "2017-09-29 success\n",
      "2017-10-31 success\n",
      "2017-11-30 success\n",
      "2017-12-29 success\n",
      "2018-01-31 success\n",
      "2018-02-28 success\n",
      "2018-03-30 success\n",
      "2018-04-27 success\n",
      "2018-05-31 success\n",
      "2018-06-29 success\n",
      "2018-07-31 success\n",
      "2018-08-31 success\n",
      "2018-09-28 success\n",
      "2018-10-31 success\n",
      "2018-11-30 success\n",
      "2018-12-28 success\n",
      "2019-01-31 success\n",
      "2019-02-28 success\n",
      "2019-03-29 success\n",
      "2019-04-30 success\n",
      "2019-05-31 success\n",
      "2019-06-28 success\n",
      "2019-07-01 success\n"
     ]
    }
   ],
   "source": [
    "# 获取因子数据\n",
    "Momentum_resid=get_Momentum_resid(date_list)\n",
    "# 保存因子的数据\n",
    "pkl_file=open('momentum_resid.plk','wb')\n",
    "pickle.dump(Momentum_resid, pkl_file, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取因子数据\n",
    "pkl_file=open('momentum_resid.plk','rb')\n",
    "Momentum_resid = pickle.load(pkl_file)\n",
    "pkl_file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 使用获取的因子值进行单因子分析\n",
    "## 设置调仓周期\n",
    "periods=20\n",
    "## 设置分层数量\n",
    "quantiles=10\n",
    "far_resid=analyze_factor(Momentum_resid.iloc[:,0],start_date=start, end_date=end, \n",
    "                         weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 储存分析后的数据\n",
    "pkl_file=open('far_resid.plk','wb')\n",
    "pickle.dump(far_resid,pkl_file,0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取分析后的数据\n",
    "pkl_file=open('far_resid.plk','rb')\n",
    "far_resid=pickle.load(pkl_file)\n",
    "pkl_file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "风格中性后的残差动量因子IC均值略高于原始动量因子，但IC_IR波动率得到有效降低，从原始的0.159下降到0.121，IC_IR也有所提升，因子的稳定性提升较为明显。但多空夏普有所下降，且单调性得分也有所下降。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IC</th>\n",
       "      <th>IC_IR</th>\n",
       "      <th>LongShort_sharpe</th>\n",
       "      <th>MONO_Score</th>\n",
       "      <th>Turnover</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1M</th>\n",
       "      <td>-0.045512</td>\n",
       "      <td>-0.066641</td>\n",
       "      <td>-7.728916</td>\n",
       "      <td>2.012446</td>\n",
       "      <td>0.930497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mono_1M</th>\n",
       "      <td>0.039852</td>\n",
       "      <td>0.056369</td>\n",
       "      <td>8.450311</td>\n",
       "      <td>1.876048</td>\n",
       "      <td>0.930611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Neu_1M</th>\n",
       "      <td>-0.049441</td>\n",
       "      <td>-0.068072</td>\n",
       "      <td>-8.622452</td>\n",
       "      <td>2.194422</td>\n",
       "      <td>0.929800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1M_resid</th>\n",
       "      <td>-0.061575</td>\n",
       "      <td>-0.099514</td>\n",
       "      <td>-8.417649</td>\n",
       "      <td>1.708907</td>\n",
       "      <td>0.922375</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                IC     IC_IR  LongShort_sharpe  MONO_Score  Turnover\n",
       "1M       -0.045512 -0.066641         -7.728916    2.012446  0.930497\n",
       "Mono_1M   0.039852  0.056369          8.450311    1.876048  0.930611\n",
       "Neu_1M   -0.049441 -0.068072         -8.622452    2.194422  0.929800\n",
       "1M_resid -0.061575 -0.099514         -8.417649    1.708907  0.922375"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a=factor_report(basic_far['1M'])\n",
    "b=factor_report(mono_far['Mono_1M'])\n",
    "c=factor_report(Neu_far['Neu_1M'])\n",
    "d=factor_report(far_resid)\n",
    "\n",
    "info_df=pd.concat([a,b,c,d],axis=0)\n",
    "info_df.index=['1M','Mono_1M','Neu_1M','1M_resid']\n",
    "info_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.cm as cm\n",
    "from matplotlib.ticker import ScalarFormatter\n",
    "\n",
    "# 比较不同因子的IC时序图\n",
    "'''\n",
    "输入参数：ic为df index为日期，colum为因子名称，values为因子值\n",
    "\n",
    "'''\n",
    "def plot_contrast_ic(ic, ax=None):\n",
    "\n",
    "    ic = ic.copy()\n",
    "\n",
    "    num_plots = len(ic.columns)\n",
    "    if ax is None:\n",
    "        f, ax = plt.subplots(num_plots, 1, figsize=(18, num_plots * 7))\n",
    "        ax = np.asarray([ax]).flatten()\n",
    "\n",
    "    ymin, ymax = (None, None)\n",
    "    for a, (column_name, ic) in zip(ax, ic.iteritems()):\n",
    "        title_name = column_name\n",
    "        ic.plot(alpha=0.7, ax=a, lw=0.7, color='steelblue')\n",
    "        rolling_mean=ic.rolling(22).mean()\n",
    "        rolling_mean.plot(\n",
    "            ax=a, color='forestgreen', lw=2, alpha=0.8\n",
    "        )\n",
    "\n",
    "        a.axhline(0.0, linestyle='-', color='black', lw=1, alpha=0.8)\n",
    "        a.set(ylabel='IC', xlabel=\"\")\n",
    "        a.set_title(\"{} IC_IR波动情况\".format(title_name))\n",
    "        a.legend([\"IC\", \"1个月移动平均\"], loc='upper right')\n",
    "        a.text(\n",
    "            .05,\n",
    "            .95,\n",
    "            \"均值 {:.3f} \\n标准差 {:.3f}\".format(ic.mean(), ic.std()),\n",
    "            fontsize=16,\n",
    "            bbox={\n",
    "                'facecolor': 'white',\n",
    "                'alpha': 1,\n",
    "                'pad': 5\n",
    "            },\n",
    "            transform=a.transAxes,\n",
    "            verticalalignment='top'\n",
    "        )\n",
    "\n",
    "        curr_ymin, curr_ymax = a.get_ylim()\n",
    "        ymin = curr_ymin if ymin is None else min(ymin, curr_ymin)\n",
    "        ymax = curr_ymax if ymax is None else max(ymax, curr_ymax)\n",
    "\n",
    "    for a in ax:\n",
    "        a.set_ylim([ymin, ymax])\n",
    "\n",
    "    return ax"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "原始因子的IC_IR时序图，标准差为0.159，残差动量因子的为0.121"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x000002E16B15EA90>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x000002E16A0D0940>],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x1008 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 获取原始因子的IC数据\n",
    "a=basic_far['1M'].calc_factor_information_coefficient(method='rank')\n",
    "a.columns=['1M']\n",
    "# 获取残差动量因子\n",
    "b=far_resid.calc_factor_information_coefficient(method='rank')\n",
    "b.columns=['Resid_1M']\n",
    "# 合并\n",
    "c=pd.concat([a,b],axis=1)\n",
    "# 画图\n",
    "plot_contrast_ic(c)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从残差动量因子的分位数收益中可以看出，仅7至10分为的单调性较好，总体来说因子单调性较差"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "far_resid.plot_quantile_returns_bar(demeaned=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.改造K线下的动量因子"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "基于高频数据的K线构造新方法：目前基于高频数据可以构造很多不同 的采样切片方式，目前比较主流的方式包括：ticK等分K 线，成交量等分K 线，成交额等分 K 线，信息量等分 K 线。其中 ticK 等分 K 线，成交量等分\n",
    "K 线，成交额等分K线的构造方式顾名思义都非常直观。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](picture.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于用到1分钟数据，数据量较大，我们将时间范围调整至2017年1月1日至2019年7月31日"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 设置时间范围\n",
    "begin=datetime(2017, 1, 1)\n",
    "end=datetime(2019, 8, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "每只股票按当日的成交额/成交量4等分构造K线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def get_Candlestick(start,end):\n",
    "    # 获取交易日历\n",
    "    dateList=get_trade_days(start_date=start,end_date=end)\n",
    "    # 用于储存切片数据\n",
    "    tempList=[]\n",
    "    \n",
    "    for day in dateList:\n",
    "        # 获取股票列表\n",
    "        stocks=get_stocks('000905.XSHG',day.strftime('%Y-%m-%d'))\n",
    "        # 获取交易数据\n",
    "        data_df=get_price(stocks,end_date=day,count=4*60,frequency='1m',fields=['volume','close','money'])\n",
    "        \n",
    "        volume_df=data_df.loc['volume',:,:]\n",
    "        volume_df=volume_df.unstack()\n",
    "\n",
    "        money_df=data_df.loc['money',:,:]\n",
    "        money_df=money_df.unstack()\n",
    "\n",
    "        close_df=data_df.loc['close',:,:]\n",
    "        close_df=close_df.unstack()\n",
    "        close_df.name='close'\n",
    "            \n",
    "        # 合并切片数据\n",
    "        gr_v=volume_df.groupby(level=0,group_keys=False).apply(lambda x:get_cut_data(x))\n",
    "        gr_v.index.names=['code','time']\n",
    "\n",
    "        gr_m=money_df.groupby(level=0,group_keys=False).apply(lambda x:get_cut_data(x,'money'))\n",
    "        gr_m.index.names=['code','time']\n",
    "\n",
    "        slice_df=pd.concat([gr_v,gr_m],axis=1)\n",
    "        slice_df=pd.concat([slice_df,close_df],axis=1,join='inner')\n",
    "        \n",
    "        tempList.append(slice_df)\n",
    "        \n",
    "        print(day,'success')\n",
    "        \n",
    "    df=pd.concat(tempList)\n",
    "    \n",
    "    pkl_file=open('get_Candlestick_d.pkl','wb')\n",
    "    pickle.dump(df,pkl_file,0)\n",
    "    \n",
    "    print('已完成,以储存数据，数据名：get_Candlestick_d.pkl')\n",
    "    \n",
    "    return df\n",
    "\n",
    "# 辅助函数供get_Candlestick调用\n",
    "def get_cut_data(series,params='volume'):\n",
    "\n",
    "    a=series.copy()\n",
    "    a.name=params\n",
    "    group_name=params+'_candlestick'\n",
    "    \n",
    "    g=pd.cut(a.cumsum(),bins=4,labels=['k1','k2','k3','k4'])\n",
    "    g.name=group_name\n",
    "\n",
    "    v=pd.concat([a,g],axis=1)\n",
    "    v.drop_duplicates(group_name,keep='last',inplace=True)\n",
    "    return v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
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      "2019-07-08 success\n",
      "2019-07-09 success\n",
      "2019-07-10 success\n",
      "2019-07-11 success\n",
      "2019-07-12 success\n",
      "2019-07-15 success\n",
      "2019-07-16 success\n",
      "2019-07-17 success\n",
      "2019-07-18 success\n",
      "2019-07-19 success\n",
      "2019-07-22 success\n",
      "2019-07-23 success\n",
      "2019-07-24 success\n",
      "2019-07-25 success\n",
      "2019-07-26 success\n",
      "2019-07-29 success\n",
      "2019-07-30 success\n",
      "2019-07-31 success\n",
      "2019-08-01 success\n",
      "已完成,以储存数据，数据名：get_Candlestick_d.pkl\n"
     ]
    }
   ],
   "source": [
    "# 提取数据\n",
    "Candlestick_df=get_Candlestick(begin,end)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>volume</th>\n",
       "      <th>volume_candlestick</th>\n",
       "      <th>money</th>\n",
       "      <th>money_candlestick</th>\n",
       "      <th>close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>000006.XSHE</th>\n",
       "      <th>2016-12-30 09:59:00</th>\n",
       "      <td>509749.0</td>\n",
       "      <td>k1</td>\n",
       "      <td>4531238.0</td>\n",
       "      <td>k1</td>\n",
       "      <td>8.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-30 11:20:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>514031.0</td>\n",
       "      <td>k2</td>\n",
       "      <td>8.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-30 11:23:00</th>\n",
       "      <td>11536.0</td>\n",
       "      <td>k2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-30 14:27:00</th>\n",
       "      <td>110025.0</td>\n",
       "      <td>k3</td>\n",
       "      <td>961044.0</td>\n",
       "      <td>k3</td>\n",
       "      <td>8.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-30 15:00:00</th>\n",
       "      <td>200243.0</td>\n",
       "      <td>k4</td>\n",
       "      <td>1738800.0</td>\n",
       "      <td>k4</td>\n",
       "      <td>8.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-03 09:50:00</th>\n",
       "      <td>745252.0</td>\n",
       "      <td>k1</td>\n",
       "      <td>6659152.0</td>\n",
       "      <td>k1</td>\n",
       "      <td>8.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-03 10:09:00</th>\n",
       "      <td>89130.0</td>\n",
       "      <td>k2</td>\n",
       "      <td>794055.0</td>\n",
       "      <td>k2</td>\n",
       "      <td>8.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-03 13:11:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>126174.0</td>\n",
       "      <td>k3</td>\n",
       "      <td>8.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-03 13:12:00</th>\n",
       "      <td>7400.0</td>\n",
       "      <td>k3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-03 15:00:00</th>\n",
       "      <td>506048.0</td>\n",
       "      <td>k4</td>\n",
       "      <td>4496550.0</td>\n",
       "      <td>k4</td>\n",
       "      <td>8.89</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   volume  ...  close\n",
       "000006.XSHE 2016-12-30 09:59:00  509749.0  ...   8.88\n",
       "            2016-12-30 11:20:00       NaN  ...   8.77\n",
       "            2016-12-30 11:23:00   11536.0  ...   8.78\n",
       "            2016-12-30 14:27:00  110025.0  ...   8.74\n",
       "            2016-12-30 15:00:00  200243.0  ...   8.68\n",
       "            2017-01-03 09:50:00  745252.0  ...   8.93\n",
       "            2017-01-03 10:09:00   89130.0  ...   8.91\n",
       "            2017-01-03 13:11:00       NaN  ...   8.86\n",
       "            2017-01-03 13:12:00    7400.0  ...   8.85\n",
       "            2017-01-03 15:00:00  506048.0  ...   8.89\n",
       "\n",
       "[10 rows x 5 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Candlestick_df.sort_index().head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取数据\n",
    "pkl_file=open('get_Candlestick_d.pkl','rb')\n",
    "Candlestick_df=pickle.load(pkl_file)\n",
    "pkl_file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "改造 K线下的动量因子只有在使用等K线构造方式时才会与原始动量因子有比较大的差异，因此这里我们将主要测试等 K 线个数下不同 K 线构造的动量因子的表现。我们将K 线窗口长度设为 8，即 所有输入变量的K线窗口为 8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 等成交量K线\n",
    "## 筛选出等成交量K线\n",
    "flag=Candlestick_df['volume_candlestick'].isna()\n",
    "volume_candlestick=Candlestick_df[~flag]\n",
    "\n",
    "## 按每8根k线计算动量因子\n",
    "volume_candlestick['momentum_v']=volume_candlestick.groupby(level=0)['close'].transform(lambda x:x.pct_change(periods=8))\n",
    "## index级别整理\n",
    "volume_candlestick.index.names=['code','time']\n",
    "volume_candlestick=volume_candlestick.swaplevel('time','code')\n",
    "# convert index type\n",
    "volume_candlestick.index=pd.MultiIndex.from_tuples([(ix[0].date(),ix[1]) for ix in volume_candlestick.index.tolist()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 整理成因子分析格式\n",
    "volume_candlestick['id']=[str(ix[0])+str(ix[1]) for ix in volume_candlestick.index.tolist()]\n",
    "volume_candlestick=volume_candlestick.drop_duplicates('id',keep='last')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 因子分析\n",
    "far_volume=analyze_factor(volume_candlestick['momentum_v'],start_date='2017-01-01', end_date='2019-07-31', \n",
    "                         weight_method='avg', industry='sw_l1', quantiles=10, periods=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 等成交量K线\n",
    "## 筛选出等成交量K线\n",
    "flag=Candlestick_df['money_candlestick'].isna()\n",
    "money_candlestick=Candlestick_df[~flag]\n",
    "\n",
    "## 按每8根k线计算动量因子\n",
    "money_candlestick['momentum_m']=money_candlestick.groupby(level=0)['close'].transform(lambda x:x.pct_change(periods=8))\n",
    "## index级别整理\n",
    "money_candlestick.index.names=['code','time']\n",
    "money_candlestick=money_candlestick.swaplevel('time','code')\n",
    "# convert index type\n",
    "money_candlestick.index=pd.MultiIndex.from_tuples([(ix[0].date(),ix[1]) for ix in money_candlestick.index.tolist()])\n",
    "# 整理成因子分析格式\n",
    "money_candlestick['id']=[str(ix[0])+str(ix[1]) for ix in money_candlestick.index.tolist()]\n",
    "money_candlestick=money_candlestick.drop_duplicates('id',keep='last')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 因子分析\n",
    "far_money=analyze_factor(money_candlestick['momentum_m'],start_date='2017-01-01', end_date='2019-07-31', \n",
    "                         weight_method='avg', industry='sw_l1', quantiles=10, periods=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "等分K线的效果不是那么理想"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IC</th>\n",
       "      <th>IC_IR</th>\n",
       "      <th>LongShort_sharpe</th>\n",
       "      <th>MONO_Score</th>\n",
       "      <th>Turnover</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>volume_k</th>\n",
       "      <td>0.003153</td>\n",
       "      <td>-0.009106</td>\n",
       "      <td>-0.035026</td>\n",
       "      <td>0.046618</td>\n",
       "      <td>0.893033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>money_k</th>\n",
       "      <td>0.003071</td>\n",
       "      <td>-0.009095</td>\n",
       "      <td>-0.052895</td>\n",
       "      <td>0.072255</td>\n",
       "      <td>0.893025</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                IC     IC_IR  LongShort_sharpe  MONO_Score  Turnover\n",
       "volume_k  0.003153 -0.009106         -0.035026    0.046618  0.893033\n",
       "money_k   0.003071 -0.009095         -0.052895    0.072255  0.893025"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 改造k线因子分析汇总\n",
    "k_far={'volume_k':far_volume,'money_k':far_money}\n",
    "trans2period(k_far,20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.改造基础版动量因子"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "使用过去60个交易日风险调整后的涨跌幅作为动量因子（它和市值因子的相关性仅为0.085），其计算公式如下所示：\n",
    "\n",
    "### $$r_{60}-3000*\\sigma ^{2}$$\n",
    "\n",
    "其中$r_{60}$为60日涨跌幅，即60个交易日内的收益率;$\\sigma$为60个交易日内收益率的标准差，代表风险。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2007-01-31 success\n",
      "2007-02-28 success\n",
      "2007-03-30 success\n",
      "2007-04-30 success\n",
      "2007-05-31 success\n",
      "2007-06-29 success\n",
      "2007-07-31 success\n",
      "2007-08-31 success\n",
      "2007-09-28 success\n",
      "2007-10-31 success\n",
      "2007-11-30 success\n",
      "2007-12-28 success\n",
      "2008-01-31 success\n",
      "2008-02-29 success\n",
      "2008-03-31 success\n",
      "2008-04-30 success\n",
      "2008-05-30 success\n",
      "2008-06-30 success\n",
      "2008-07-31 success\n",
      "2008-08-29 success\n",
      "2008-09-26 success\n",
      "2008-10-31 success\n",
      "2008-11-28 success\n",
      "2008-12-31 success\n",
      "2009-01-23 success\n",
      "2009-02-27 success\n",
      "2009-03-31 success\n",
      "2009-04-30 success\n",
      "2009-05-27 success\n",
      "2009-06-30 success\n",
      "2009-07-31 success\n",
      "2009-08-31 success\n",
      "2009-09-30 success\n",
      "2009-10-30 success\n",
      "2009-11-30 success\n",
      "2009-12-31 success\n",
      "2010-01-29 success\n",
      "2010-02-26 success\n",
      "2010-03-31 success\n",
      "2010-04-30 success\n",
      "2010-05-31 success\n",
      "2010-06-30 success\n",
      "2010-07-30 success\n",
      "2010-08-31 success\n",
      "2010-09-30 success\n",
      "2010-10-29 success\n",
      "2010-11-30 success\n",
      "2010-12-31 success\n",
      "2011-01-31 success\n",
      "2011-02-28 success\n",
      "2011-03-31 success\n",
      "2011-04-29 success\n",
      "2011-05-31 success\n",
      "2011-06-30 success\n",
      "2011-07-29 success\n",
      "2011-08-31 success\n",
      "2011-09-30 success\n",
      "2011-10-31 success\n",
      "2011-11-30 success\n",
      "2011-12-30 success\n",
      "2012-01-31 success\n",
      "2012-02-29 success\n",
      "2012-03-30 success\n",
      "2012-04-27 success\n",
      "2012-05-31 success\n",
      "2012-06-29 success\n",
      "2012-07-31 success\n",
      "2012-08-31 success\n",
      "2012-09-28 success\n",
      "2012-10-31 success\n",
      "2012-11-30 success\n",
      "2012-12-31 success\n",
      "2013-01-31 success\n",
      "2013-02-28 success\n",
      "2013-03-29 success\n",
      "2013-04-26 success\n",
      "2013-05-31 success\n",
      "2013-06-28 success\n",
      "2013-07-31 success\n",
      "2013-08-30 success\n",
      "2013-09-30 success\n",
      "2013-10-31 success\n",
      "2013-11-29 success\n",
      "2013-12-31 success\n",
      "2014-01-30 success\n",
      "2014-02-28 success\n",
      "2014-03-31 success\n",
      "2014-04-30 success\n",
      "2014-05-30 success\n",
      "2014-06-30 success\n",
      "2014-07-31 success\n",
      "2014-08-29 success\n",
      "2014-09-30 success\n",
      "2014-10-31 success\n",
      "2014-11-28 success\n",
      "2014-12-31 success\n",
      "2015-01-30 success\n",
      "2015-02-27 success\n",
      "2015-03-31 success\n",
      "2015-04-30 success\n",
      "2015-05-29 success\n",
      "2015-06-30 success\n",
      "2015-07-31 success\n",
      "2015-08-31 success\n",
      "2015-09-30 success\n",
      "2015-10-30 success\n",
      "2015-11-30 success\n",
      "2015-12-31 success\n",
      "2016-01-29 success\n",
      "2016-02-29 success\n",
      "2016-03-31 success\n",
      "2016-04-29 success\n",
      "2016-05-31 success\n",
      "2016-06-30 success\n",
      "2016-07-29 success\n",
      "2016-08-31 success\n",
      "2016-09-30 success\n",
      "2016-10-31 success\n",
      "2016-11-30 success\n",
      "2016-12-30 success\n",
      "2017-01-26 success\n",
      "2017-02-28 success\n",
      "2017-03-31 success\n",
      "2017-04-28 success\n",
      "2017-05-31 success\n",
      "2017-06-30 success\n",
      "2017-07-31 success\n",
      "2017-08-31 success\n",
      "2017-09-29 success\n",
      "2017-10-31 success\n",
      "2017-11-30 success\n",
      "2017-12-29 success\n",
      "2018-01-31 success\n",
      "2018-02-28 success\n",
      "2018-03-30 success\n",
      "2018-04-27 success\n",
      "2018-05-31 success\n",
      "2018-06-29 success\n",
      "2018-07-31 success\n",
      "2018-08-31 success\n",
      "2018-09-28 success\n",
      "2018-10-31 success\n",
      "2018-11-30 success\n",
      "2018-12-28 success\n",
      "2019-01-31 success\n",
      "2019-02-28 success\n",
      "2019-03-29 success\n",
      "2019-04-30 success\n",
      "2019-05-31 success\n",
      "2019-06-28 success\n",
      "2019-07-01 success\n"
     ]
    }
   ],
   "source": [
    "# 之前get_momentum_facto已经包含此部分计算，直接使用即可\n",
    "datas=get_momentum_factor(date_list,61,False)\n",
    "\n",
    "# 储存数据\n",
    "pkl_file=open('datas.pkl','wb')\n",
    "pickle.dump(datas,pkl_file,0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取数据\n",
    "pkl_file=open('datas.pkl','rb')\n",
    "datas=pickle.load(pkl_file)\n",
    "pkl_file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 使用获取的因子值进行单因子分析\n",
    "## 设置调仓周期\n",
    "periods=20\n",
    "## 设置分层数量\n",
    "quantiles=10\n",
    "far_datas=analyze_factor(datas['momentum'],start_date=start, end_date=end, \n",
    "                         weight_method='avg', industry='sw_l1', quantiles=quantiles, periods=periods)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 储存分析文件\n",
    "pkl_file=open('far_datas.pkl','wb')\n",
    "pickle.dump(far_datas,pkl_file,0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取分析文件\n",
    "pkl_file=open('far_datas.pkl','rb')\n",
    "far_datas=pickle.load(pkl_file)\n",
    "pkl_file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IC</th>\n",
       "      <th>IC_IR</th>\n",
       "      <th>LongShort_sharpe</th>\n",
       "      <th>MONO_Score</th>\n",
       "      <th>Turnover</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>period_20</th>\n",
       "      <td>0.025917</td>\n",
       "      <td>0.052538</td>\n",
       "      <td>2.826667</td>\n",
       "      <td>2.59303</td>\n",
       "      <td>0.914342</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 IC     IC_IR  LongShort_sharpe  MONO_Score  Turnover\n",
       "period_20  0.025917  0.052538          2.826667     2.59303  0.914342"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看因子报告\n",
    "factor_report(far_datas)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下图为因子的十分位**超额**平均收益图，可以看到因子单调性不高，可以看到较小的因子超额收益反而更强"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "far_datas.plot_quantile_returns_bar(demeaned=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "各分位数每日累积超额收益图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "far_datas.plot_cumulative_returns_by_quantile(period=20, demeaned=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "多空收益如下"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "far_datas.plot_cumulative_returns(period=20, demeaned=True, group_adjust=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "far_datas.plot_ic_ts(method='rank')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 结论"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. 结合均线的趋势动量因子\n",
    "\n",
    "    动量因子构造时所使用的数据仅为起始节点和末尾节点的股价数据，对于 期间的股价信息并未充分反应，因此我们尝试采用均线的思路，构造更好的反应股价趋势的趋势动量因子。\n",
    "\n",
    "    **趋势动量因子均具有很高的单调性，单调性得分均可以超过3分，Mono_12M的多空夏普也很高，整体IC较原版有所提升。**\n",
    "\n",
    "\n",
    "2. 剥离流动性因素后的提纯动量因子\n",
    "\n",
    "    散户集中程度或者说流动性因素是影响动量因子效果的一个重要变量。因 此，我们采用截面中性化的方法，将衡量散户集中程度的流动性因素从原始动量因子中剥离。\n",
    "\n",
    "    **对比基础动量因子，多空收益有所提高**\n",
    "\n",
    "\n",
    "3. 风格中性后的残差动量因子\n",
    "\n",
    "    Blitz D构建了一个基于残差的动量策略(residual momentum)，并指出残差 动量模型在诸多方面的表现都显著优于传统的价格动量。我们从短期动量入手，采用当期残差变量作为剔除市场风格影响后的特质收益动量因子。\n",
    "\n",
    "    **IC,IC_IR对比其他动量因子有所提高**\n",
    "    \n",
    "    \n",
    "4. 改造K线下的动量因子\n",
    "\n",
    "    对比起来改善并不明显..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
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    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  },
  "toc": {
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   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
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   "toc_window_display": true
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